@article {7032, title = {A Digital 3D Reference Atlas Reveals Cellular Growth Patterns Shaping the Arabidopsis Ovule}, journal = {eLife}, year = {2021}, doi = {10.7554/eLife.63262}, author = {Vijayan, A. and Tofanelli, R and Strauss, S and Cerrone, L and Wolny, A and Strohmeier, J and Kreshuk, A and Fred A. Hamprecht and Smith, R S and Schneitz, K} } @article {6333, title = {End-to-End Learning of Decision Trees and Forests}, journal = {International Journal of Computer Vision}, volume = {128}, year = {2020}, pages = {997-1011}, doi = {10.1007/s11263-019-01237-6}, author = {Hehn, TM and Kooij, J F P and Fred A. Hamprecht} } @proceedings {6318, title = {Deep Active Learning with Adaptive Acquisition}, year = {2019}, pages = {2470-2476}, doi = { 10.24963/ijcai.2019/343}, author = {Manuel Hau{\ss}mann and Fred A. Hamprecht and Kandemir, M.} } @proceedings {6302, title = {End-to-End Learned Random Walker for Seeded Image Segmentation}, year = {2019}, pages = {12559-12568}, doi = { 10.1109/CVPR.2019.01284}, author = {Cerrone, L and Zeilmann, A and Fred A. Hamprecht} } @article {6334, title = {ilastik: interactive machine learning for (bio)image analysis}, journal = {Nature Methods}, volume = {16}, year = {2019}, pages = {1226-1232}, doi = {10.1038/s41592-019-0582-9}, author = {Stuart Berg and Kutra, D and Kroeger, T and Christoph N. Straehle and Bernhard X. Kausler and Haubold, C. and Schiegg, M and Ales, J and Thorsten Beier and Rudy, M and Eren, K and Cervantes, JI and Xu, B and Beuttenm{\"u}ller, F and Wolny, A and Zhang, C and Ullrich K{\"o}the and Fred A. Hamprecht and Kreshuk, A} } @proceedings {6288, title = {LeMoNADe: Learned Motif and Neuronal Assembly Detection in calcium imaging videos}, year = {2019}, author = {Kirschbaum, E. and Manuel Hau{\ss}mann and Wolf, S and Sonntag, H and Schneider, J and Elzoheiry, S and Kann, O and Durstewitz, D and Fred A. Hamprecht} } @proceedings {6317, title = {Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation}, year = {2019}, pages = {563-573}, author = {Manuel Hau{\ss}mann and Fred A. Hamprecht and Kandemir, M.} } @proceedings {6297, title = {End-to-end Learning of Deterministic Decision Trees}, volume = {LNCS 11269}, year = {2018}, pages = {612-627}, publisher = {Springer}, doi = {10.1007/978-3-030-12939-2_42}, author = {Hehn, T and Fred A. Hamprecht} } @proceedings {6272, title = {Essentially No Barriers in Neural Network Energy Landscape}, volume = {80}, year = {2018}, pages = {1308--1317}, author = {Draxler, F and Veschgini, K and Salmhofer, M and Fred A. Hamprecht} } @proceedings {6234, title = {Learning Steerable Filters for Rotation Equivariant CNNs}, year = {2018}, pages = {849-858}, doi = {10.1109/CVPR.2018.00095}, author = {Maurice Weiler and Fred A. Hamprecht and Martin Storath} } @proceedings {6275, title = {The Mutex Watershed: Efficient, Parameter-Free Image Partitioning}, year = {2018}, pages = {571-587}, publisher = {Springer}, doi = {10.1007/978-3-030-01225-0_34}, author = {Wolf, S and Pape, C and Bailoni, A and Rahaman, N and Kreshuk, A. and Ullrich K{\"o}the and Fred A. Hamprecht} } @conference {Wolf2018, title = {The Mutex Watershed: Efficient, Parameter-Free Image Partitioning}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {11208 LNCS}, year = {2018}, month = {apr}, pages = {571{\textendash}587}, abstract = {Image partitioning, or segmentation without semantics, is the task of decomposing an image into distinct segments; or equivalently, the task of detecting closed contours in an image. Most prior work either requires seeds, one per segment; or a threshold; or formulates the task as an NP-hard signed graph partitioning problem. Here, we propose an algorithm with empirically linearithmic complexity. Unlike seeded watershed, the algorithm can accommodate not only attractive but also repulsive cues, allowing it to find a previously unspecified number of segments without the need for explicit seeds or a tunable threshold. The algorithm itself, which we dub {\textquotedblleft}Mutex Watershed{\textquotedblright}, is closely related to a minimal spanning tree computation. It is deterministic and easy to implement. When presented with short-range attractive and long-range repulsive cues from a deep neural network, the Mutex Watershed gives results that currently define the state-of-the-art in the competitive ISBI 2012 EM segmentation benchmark. These results are also better than those obtained from other recently proposed clustering strategies operating on the very same network outputs.}, isbn = {9783030012243}, issn = {16113349}, doi = {10.1007/978-3-030-01225-0_34}, url = {http://arxiv.org/abs/1904.12654}, author = {Wolf, Steffen and Pape, Constantin and Bailoni, Alberto and Rahaman, Nasim and Kreshuk, Anna and Ullrich K{\"o}the and Fred A. Hamprecht} } @article {6314, title = {On the spectral bias of deep neural networks}, journal = {arXiv preprint arXiv:1806.08734}, year = {2018}, author = {Rahaman, N and Arpit, D and Baratin, A and Draxler, F and Lin, M and Fred A. Hamprecht and Bengio, Y and Courville, A} } @article {6180, title = {Active machine learning for training an event classification}, journal = {Patent, Patent Number WO2017032775 A1}, year = {2017}, author = {Kandemir, M. and Fred A. Hamprecht and Wojek, C. and Schmidt, U.} } @proceedings {6204, title = {Cost-efficient Gradient Boosting}, year = {2017}, author = {Peter, S. and Ferran Diego and Fred A. Hamprecht and Nadler, B} } @proceedings {6182, title = {Diverse M-best Solutions by Dynamic Programming}, volume = {LNCS 10496}, year = {2017}, pages = {255-267}, publisher = {Springer}, doi = {10.1007/978-3-319-66709-6_21}, author = {Haubold, C. and Uhlmann, V and Michael Unser and Fred A. Hamprecht} } @article {6209, title = {Diverse Shortest Paths for Bioimage Analysis}, journal = {Bioinformatics}, year = {2017}, pages = {1-3}, doi = {10.1093/bioinformatics/btx621}, author = {Uhlmann, V and Haubold, C. and Fred A. Hamprecht and Michael Unser} } @article {6212, title = {Learned Watershed: End-to-End Learning of Seeded Segmentation}, year = {2017}, pages = {2030-2038}, author = {Wolf, S and Schott, L and Ullrich K{\"o}the and Fred A. Hamprecht} } @article {6181, title = {Maschinelles Lernen}, journal = {Patent, Patent Number WO2017032775A1}, year = {2017}, author = {Kandemir, M. and Fred A. Hamprecht and Wojek, C and Schmidt, U.} } @article {6122, title = {Multicut brings automated neurite segmentation closer to human performance}, journal = {Nature Methods}, volume = {14}, year = {2017}, pages = {101-102}, doi = {10.1038/nmeth.4151}, url = {http://rdcu.be/oVDQ}, author = {Thorsten Beier and Pape, C and Rahaman, N and Prange, T and Stuart Berg and Bock, D and A. Cardona and G. W. Knott and Plaza, S M and Scheffer, L K and Ullrich K{\"o}the and Kreshuk, A and Fred A. Hamprecht} } @article {6178, title = {Neuron Segmentation with High-Level Biological Priors}, journal = {IEEE Transactions on Medical Imaging}, volume = {37}, year = {2017}, chapter = {829-839}, doi = {10.1109/TMI.2017.2712360}, author = {Krasowki, N and Thorsten Beier and G. W. Knott and Ullrich K{\"o}the and Fred A. Hamprecht and Kreshuk, A.} } @article {6210, title = {An Objective Comparison of Cell Tracking Algorithms}, journal = {Nature Methods}, volume = {14}, year = {2017}, pages = {1141-1152}, doi = {10.1038/NMETH.447}, author = {Ulman, V. and Ma{\v s}ka, M. and Magnusson, K .E. G. and Ronneberger, O. and Haubold, C. and Harder, N. and Matula, P. and Matula, P. and Svoboda, D. and Radojevic, M. and Smal, I. and Karl Rohr and Jald{\'e}n, J. and Blau, H. M. and Dzyubachyk, O. and Lelieveldt, B. and Xiao, P. and Li, Y. and Cho, S-Y. and Dufour, A. and Olivo-Marin, J. C. and Reyes-Aldasoro, C. C. and Solis-Lemus, J. A. and Bensch, R. and Brox, T. and Stegmaier, J. and Mikut, R. and Wolf, S. and Fred A. Hamprecht and Esteves, T. and Quelhas, P. and Demirel, {\"O}. and Malstr{\"o}m, L. and Jug, F. and Toman{\v c}{\'a}k, P. and Meijering, E. and Mu{\~n}oz-Barrutia, A. and Kozubek, M. and Ortiz-de-Solorzano, C.} } @proceedings {6205, title = {Sparse convolutional coding for neuronal assembly detection}, year = {2017}, author = {Peter, S. and Kirschbaum, E. and M. Both and Campbell, L. A. and Harvey, B. K. and Heins, C. and Durstewitz, D. and Ferran Diego and Fred A. Hamprecht} } @proceedings {6140, title = {Variational Bayesian Multiple Instance Learning with Gaussian Processes}, year = {2017}, pages = {6570-6579}, doi = {10.1109/CVPR.2017.93}, author = {Manuel Hau{\ss}mann and Fred A. Hamprecht and Kandemir, M} } @proceedings {6078, title = {An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem}, volume = {LNCS 9906}, year = {2016}, pages = {715-730}, publisher = {Springer}, doi = { 10.1007/978-3-319-46475-6_44}, author = {Thorsten Beier and Bj{\"o}rn Andres and Ullrich K{\"o}the and Fred A. Hamprecht} } @proceedings {6080, title = {Gaussian process density counting from weak supervision}, volume = {LNCS 9905}, year = {2016}, pages = {365-380 }, publisher = {Springer}, doi = { 10.1007/978-3-319-46448-0_22}, author = {M. von Borstel and Kandemir, M and Schmidt, P and Rao, M and Rajamani, K and Fred A. Hamprecht} } @proceedings {6077, title = {A Generalized Successive Shortest Paths Solver for Tracking Dividing Targets}, volume = {LNCS 9911}, year = {2016}, pages = {566-582}, publisher = {Springer}, doi = {10.1007/978-3-319-46478-7_35}, author = {Haubold, C. and Ales, J and Wolf, S and Fred A. Hamprecht} } @article {6119, title = {Imagining the future of bioimage analysis}, journal = {Nature Biotechnology}, volume = {34}, year = {2016}, pages = {1250-1255}, doi = {10.1038/nbt.3722}, author = {Meijering, E and Carpenter, A E and Peng, Hanchuan and Fred A. Hamprecht and Olivo-Marin, J} } @proceedings {6081, title = {Learning Diverse Models: The Coulomb Structured Support Vector Machine}, volume = {LNCS 9907}, year = {2016}, pages = {585-599}, publisher = {Springer}, doi = { 10.1007/978-3-319-46487-9_36}, author = {Schiegg, M. and Ferran Diego and Fred A. Hamprecht} } @inbook {6055, title = {Segmenting and Tracking Multiple Dividing Targets Using ilastik}, booktitle = {Focus on Bio-Image Informatics}, series = {Advances in Anatomy, Embryology and Cell Biology}, volume = {219}, year = {2016}, pages = {199-229}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-319-28549-8_8}, author = {Haubold, C. and Schiegg, M. and Kreshuk, A. and Stuart Berg and Ullrich K{\"o}the and Fred A. Hamprecht} } @proceedings {6063, title = {Structured Regression Gradient Boosting}, year = {2016}, pages = {1459-1467}, doi = { 10.1109/CVPR.2016.162}, author = {Ferran Diego and Fred A. Hamprecht} } @proceedings {6079, title = {Variational weakly-supervised Gaussian processes}, year = {2016}, author = {Kandemir, M and Manuel Hau{\ss}mann and Ferran Diego and Rajamani, K and van der Laak, J and Fred A. Hamprecht} } @article {6033, title = {Virtual Raters for Reproducible and Objective Assessments in Radiology}, journal = {Nature Scientific Reports}, volume = {6}, year = {2016}, doi = {10.1038/srep25007}, author = {Kleesiek, J. and Petersen, J. and D{\"o}ring, M. and Maier-Hein, K. and Ullrich K{\"o}the and Wick, W. and Fred A. Hamprecht and M. Bendszus and A. Biller} } @article {kreshuk_15_automated, title = {Automated Tracing of Myelinated Axons and Detection of the Nodes of Ranvier in Serial Images of Peripheral Nerves}, journal = {Journal of Microscopy}, volume = {259 (2)}, year = {2015}, pages = {143-154}, doi = {10.1111/jmi.12266}, author = {Anna Kreshuk and Walecki, R. and Ullrich K{\"o}the and Gierthm{\"u}hlen, M. and Plachta, D. and Genoud, C. and Haastert-Talini, K. and Fred A. Hamprecht} } @proceedings {kandemir_15_cell, title = {Cell event detection in phase-contrast microscopy sequences from few annotations}, volume = {LNCS 9351}, year = {2015}, pages = {316-323}, publisher = {Springer}, doi = {10.1007/978-3-319-24574-4_38}, author = {Kandemir, M. and Fred A. Hamprecht} } @article {kappes_15_comparative, title = {A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems}, journal = {International Journal of Computer Vision}, year = {2015}, note = {1}, pages = {1-30}, doi = {10.1007/s11263-015-0809-x}, author = {J{\"o}rg H. Kappes and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, S. and Dhruv Batra and Kim, S. and Bernhard X. Kausler and Thorben Kr{\"o}ger and Lellmann, J. and Komodakis, N. and Savchynskyy, B. and Carsten Rother} } @article {Kappes2015, title = {A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems}, journal = {Int.~J.~Comp.~Vision}, year = {2015}, note = {in press (preprint: arXiv:1404.0533)}, author = {J{\"o}rg H. Kappes and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, S. and Dhruv Batra and Kim, S. and Bernhard X. Kausler and Thorben Kr{\"o}ger and Lellmann, J. and Komodakis, N. and Savchynskyy, B. and Carsten Rother} } @article {Kappes2015, title = {A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems}, journal = {International Journal of Computer Vision}, volume = {115}, number = {2}, year = {2015}, pages = {155{\textendash}184}, abstract = {Szeliski et al. published an influential study in 2006 on energy minimization methods for Markov random fields. This study provided valuable insights in choosing the best optimization technique for certain classes of problems. While these insights remain generally useful today, the phenomenal success of random field models means that the kinds of inference problems that have to be solved changed significantly. Specifically, the models today often include higher order interactions, flexible connectivity structures, large label-spaces of different cardinalities, or learned energy tables. To reflect these changes, we provide a modernized and enlarged study. We present an empirical comparison of more than 27 state-of-the-art optimization techniques on a corpus of 2453 energy minimization instances from diverse applications in computer vision. To ensure reproducibility, we evaluate all methods in the OpenGM 2 framework and report extensive results regarding runtime and solution quality. Key insights from our study agree with the results of Szeliski et al. for the types of models they studied. However, on new and challenging types of models our findings disagree and suggest that polyhedral methods and integer programming solvers are competitive in terms of runtime and solution quality over a large range of model types.}, keywords = {Benchmark, Combinatorial optimization, Discrete graphical models}, issn = {15731405}, doi = {10.1007/s11263-015-0809-x}, url = {http://hci.iwr.uni-heidelberg.de/opengm2/}, author = {Kappes, J{\"o}rg H and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, Sebastian and Dhruv Batra and Kim, Sungwoong and Kausler, Bernhard X and Kr{\"o}ger, Thorben and Lellmann, Jan and Komodakis, Nikos and Savchynskyy, Bogdan and Carsten Rother} } @article {Kappes2015a, title = {A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems}, journal = {International Journal of Computer Vision}, volume = {115}, number = {2}, year = {2015}, pages = {155{\textendash}184}, abstract = {Szeliski et al. published an influential study in 2006 on energy minimization methods for Markov random fields. This study provided valuable insights in choosing the best optimization technique for certain classes of problems. While these insights remain generally useful today, the phenomenal success of random field models means that the kinds of inference problems that have to be solved changed significantly. Specifically, the models today often include higher order interactions, flexible connectivity structures, large label-spaces of different cardinalities, or learned energy tables. To reflect these changes, we provide a modernized and enlarged study. We present an empirical comparison of more than 27 state-of-the-art optimization techniques on a corpus of 2453 energy minimization instances from diverse applications in computer vision. To ensure reproducibility, we evaluate all methods in the OpenGM 2 framework and report extensive results regarding runtime and solution quality. Key insights from our study agree with the results of Szeliski et al. for the types of models they studied. However, on new and challenging types of models our findings disagree and suggest that polyhedral methods and integer programming solvers are competitive in terms of runtime and solution quality over a large range of model types.}, keywords = {Benchmark, Combinatorial optimization, Discrete graphical models}, isbn = {25164671.25}, issn = {15731405}, doi = {10.1007/s11263-015-0809-x}, author = {Kappes, J{\"o}rg H and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, Sebastian and Dhruv Batra and Kim, Sungwoong and Kausler, Bernhard X and Kr{\"o}ger, Thorben and Lellmann, Jan and Komodakis, Nikos and Savchynskyy, Bogdan and Carsten Rother} } @article {Kappes2015b, title = {A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems}, journal = {International Journal of Computer Vision}, volume = {115}, number = {2}, year = {2015}, pages = {155{\textendash}184}, abstract = {Szeliski et al. published an influential study in 2006 on energy minimization methods for Markov random fields. This study provided valuable insights in choosing the best optimization technique for certain classes of problems. While these insights remain generally useful today, the phenomenal success of random field models means that the kinds of inference problems that have to be solved changed significantly. Specifically, the models today often include higher order interactions, flexible connectivity structures, large label-spaces of different cardinalities, or learned energy tables. To reflect these changes, we provide a modernized and enlarged study. We present an empirical comparison of more than 27 state-of-the-art optimization techniques on a corpus of 2453 energy minimization instances from diverse applications in computer vision. To ensure reproducibility, we evaluate all methods in the OpenGM 2 framework and report extensive results regarding runtime and solution quality. Key insights from our study agree with the results of Szeliski et al. for the types of models they studied. However, on new and challenging types of models our findings disagree and suggest that polyhedral methods and integer programming solvers are competitive in terms of runtime and solution quality over a large range of model types.}, keywords = {Benchmark, Combinatorial optimization, Discrete graphical models}, issn = {15731405}, doi = {10.1007/s11263-015-0809-x}, author = {Kappes, J{\"o}rg H and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, Sebastian and Dhruv Batra and Kim, Sungwoong and Kausler, Bernhard X and Kr{\"o}ger, Thorben and Lellmann, Jan and Komodakis, Nikos and Savchynskyy, Bogdan and Carsten Rother} } @proceedings {6003, title = {The Deep Feed-Forward Gaussian Process: An Effective Generalization to Covariance Priors}, volume = {44}, year = {2015}, pages = {145-159}, author = {Kandemir, M and Fred A. Hamprecht} } @conference {beier_15_fusion, title = {Fusion Moves for Correlation Clustering}, booktitle = {CVPR. Proceedings}, year = {2015}, note = {1}, pages = {3507-3516}, author = {Thorsten Beier and Fred A. Hamprecht and J{\"o}rg H. Kappes} } @article {schiegg_15_graphical, title = {Graphical Model for Joint Segmentation and Tracking of Multiple Dividing Cell}, journal = {Bioinformatics}, volume = {31}, number = {6}, year = {2015}, note = {1}, pages = {948-956}, doi = {10.1093/bioinformatics/btu764}, url = {http://bioinformatics.oxfordjournals.org/content/early/2014/11/17/bioinformatics.btu764.full.pdf?keytype=ref\&ijkey=mTXWsiFrci7R8tc}, author = {Schiegg, M. and Hanslovsky, P. and Haubold, C. and Ullrich K{\"o}the and Hufnagel, L. and Fred A. Hamprecht} } @conference {krasowski_15_improving, title = {Improving 3D EM Data Segmentation by Joint Optimization over Boundary Evidence and Biological Priors}, booktitle = {12th {IEEE} International Symposium on Biomedical Imaging, {ISBI} 2015, Brooklyn, NY, USA, April 16-19, 2015}, year = {2015}, note = {1}, pages = {536-539}, doi = {10.1109/ISBI.2015.7163929}, author = {Niko Krasowski and Thorsten Beier and G. W. Knott and Ullrich K{\"o}the and Fred A. Hamprecht and Anna Kreshuk} } @conference {funke_15_learning, title = {Learning to Segment: Training Hierarchical Segmentation under a Topological Loss}, booktitle = {MICCAI. Proceedings, Part III}, volume = {9351}, year = {2015}, pages = {268-275}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-319-24574-4}, author = {Funke, J. and Fred A. Hamprecht and Zhang, C.}, editor = {Frangi, A. et al.} } @conference {schiegg_15_proof-reading, title = {Proof-reading Guidance in Cell Tracking by Sampling from Tracking-by-assignment Models}, booktitle = {ISBI. Proceedings}, year = {2015}, note = {1}, pages = {394-398}, doi = {10.1109/ISBI.2015.7163895}, author = {Schiegg, M. and Heuer, B. and Haubold, C. and Wolf, S. and Ullrich K{\"o}the and Fred A. Hamprecht} } @article {cali_15_three-dimensional, title = {Three-dimensional immersive virtual reality for studying cellular compartments in 3D models from EM preparations of neural tissues}, journal = {Journal of Comparative Neurology}, volume = {524}, year = {2015}, pages = {23-38}, doi = {10.1002/cne.23852}, author = {Cali, C. and Baghabra, J. and Boges, D. J. and Holst, G. R. and Anna Kreshuk and Fred A. Hamprecht and Srinivasan, M. and Lehv{\"a}slaiho, H. and Magistretti, P. J.} } @proceedings {kreshuk_15_who, title = {Who is talking to whom: synaptic partner detection in anisotropic volumes of insect brain}, volume = {LNCS 9349}, year = {2015}, pages = {661-668}, publisher = {Springer}, doi = {10.1007/978-3-319-24553-9_81}, author = {Anna Kreshuk and Funke, J. and A. Cardona and Fred A. Hamprecht} } @article {lou_14_active, title = {Active Structured Learning for Cell Tracking: Algorithm, Framework and Usability}, journal = {IEEE Transactions on Medical Imaging}, volume = {33 (4)}, year = {2014}, pages = {849-860}, doi = {10.1109/TMI.2013.2296937}, author = {Lou, X. and Schiegg, M. and Fred A. Hamprecht} } @conference {kroeger_14_asymmetric, title = {Asymmetric Cuts: Joint Image Labeling and Partitioning}, booktitle = {Pattern Recognition - 36th German Conference, {GCPR} 2014, M{\"u}nster, Germany, September 2-5, 2014, Proceedings}, year = {2014}, doi = {10.1007/978-3-319-11752-2_16}, url = {http://dx.doi.org/10.1007/978-3-319-11752-2_16}, author = {Thorben Kr{\"o}ger and J{\"o}rg H. Kappes and Thorsten Beier and Ullrich K{\"o}the and Fred A. Hamprecht} } @conference {Kroeger-2014, title = {Asymmetric Cuts: Joint Image Labeling and Partitioning}, booktitle = {36th German Conference on Pattern Recognition}, year = {2014}, author = {Kr{\"o}ger, Thorben and Kappes, J{\"o}rg H. and Thorsten Beier and K{\"o}the, Ullrich and Fred A. Hamprecht} } @conference {tek_14_automated, title = {Automated Cell Nucleus Detection for Large-Volume Electron Microscopy of Neural Tissue}, booktitle = {ISBI. Proceedings}, year = {2014}, note = {1}, pages = {69-72}, doi = {10.1109/ISBI.2014.6867811}, author = {Tek, B. F. and Thorben Kr{\"o}ger and Mikula, S. and Fred A. Hamprecht} } @article {kreshuk_14_automated, title = {Automated Detection of Synapses in Serial Section Transmission Electron Microscopy Image Stacks}, journal = {PLoS ONE}, volume = {9}, year = {2014}, note = {1}, pages = {2}, doi = {10.1371/journal.pone.0087351}, author = {Anna Kreshuk and Ullrich K{\"o}the and Pax, E. and Bock, D. D. and Fred A. Hamprecht} } @conference {zhang_14_cell, title = {Cell detection and segmentation using correlation clustering}, booktitle = {MICCAI. Proceedings}, number = {8673}, year = {2014}, note = {1}, pages = {9-16}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-319-10404-1_2}, author = {Zhang, C. and Julian Yarkony and Fred A. Hamprecht} } @article {kappes_14_comparative, title = {A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems}, journal = {CoRR}, year = {2014}, note = {1}, url = {http://arxiv.org/abs/1404.0533}, author = {J{\"o}rg H. Kappes and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, S. and Dhruv Batra and Kim, S. and Bernhard X. Kausler and Thorben Kr{\"o}ger and Lellmann, J. and Komodakis, N. and Savchynskyy, B. and Carsten Rother} } @article {kappes-1014-bench-arxiv, title = {A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems}, journal = {CoRR}, volume = {abs/1404.0533}, year = {2014}, url = {http://hci.iwr.uni-heidelberg.de/opengm2/}, author = {J{\"o}rg H. Kappes and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, Sebastian and Dhruv Batra and Kim, Sungwoong and Bernhard X. Kausler and Thorben Kr{\"o}ger and Lellmann, Jan and Komodakis, Nikos and Savchynskyy, Bogdan and Carsten Rother} } @article {kandemir_14_computer-aided, title = {Computer-aided diagnosis from weak supervision: A benchmarking study}, journal = {Computerized Medical Imaging and Graphics}, volume = {42}, year = {2014}, note = {1}, pages = {44-50}, doi = {10.1016/j.compmedimag.2014.11.010}, author = {Kandemir, M. and Fred A. Hamprecht} } @conference {beier_14_cut, title = {Cut, Glue and Cut: A Fast, Approximate Solver for Multicut Partitioning}, booktitle = {2014 {IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR} 2014, Columbus, OH, USA, June 23-28, 2014}, year = {2014}, doi = {10.1109/CVPR.2014.17}, url = {http://dx.doi.org/10.1109/CVPR.2014.17}, author = {Thorsten Beier and Thorben Kr{\"o}ger and J{\"o}rg H. Kappes and Ullrich K{\"o}the and Fred A. Hamprecht} } @conference {decker_14_detecting, title = {Detecting individual body parts improves mouse behavior classification}, booktitle = {Workshop on visual observation and analysis of Vertebrate And Insect Behavior (VAIB), 22nd International Conference on Pattern Recognition (ICPR). Proceedings}, year = {2014}, note = {1}, author = {Decker, C. and Fred A. Hamprecht} } @article {kandemir_14_digital, title = {Digital Pathology: Multiple instance learning can detect Barrett{\textquoteright}scancer}, year = {2014}, pages = {1348-1351}, doi = {10.1109/ISBI.2014.6868127}, author = {Kandemir, M. and Feuchtinger, A. and Walch, A. and Fred A. Hamprecht} } @conference {kandemir_14_empowering, title = {Empowering multiple instance histopathology cancer diagnosis by cell graphs}, booktitle = {MICCAI. Proceedings}, volume = {8674}, year = {2014}, note = {1}, pages = {228-235}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-319-10470-6_29}, author = {Kandemir, M. and Zhang, C. and Fred A. Hamprecht} } @conference {kandemir:MICCAI:2014, title = {Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures}, booktitle = {Medical Image Computing and Computer-Assisted Intervention}, year = {2014}, pages = {154--161}, publisher = {Springer}, organization = {Springer}, author = {Kandemir, M and Rubio, J. C. and Schmidt, U. and Wojek, C. and Welbl, J. and Bj{\"o}rn Ommer and Fred A. Hamprecht} } @conference {kandemir_14_event, title = {Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures}, booktitle = {MICCAI. Proceedings}, number = {8674}, year = {2014}, note = {1}, pages = {154-161}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-319-10470-6_20}, author = {Kandemir, M. and Rubio, J. C. and Schmidt, U. and Welbl, J. and Bj{\"o}rn Ommer and Fred A. Hamprecht} } @article {lindner_14_hexicon, title = {Hexicon 2: Automated Processing of Hydrogen-Deuterium Exchange Mass Spectrometry Data with Improved Deuteration Distribution Estimation}, journal = {Journal of The American Society for Mass Spectrometry}, volume = {25}, year = {2014}, note = {1}, pages = {1018-1028}, doi = {10.1007/s13361-014-0850-y}, author = {Lindner, R. and Lou, X. and Reinstein, J. and Shoeman, R. L. and Fred A. Hamprecht and Winkler, A.} } @conference {kleesiek_14_ilastik, title = {ilastik for Multi-modal Brain Tumor Segmentation}, booktitle = {MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, 3rdplace}, year = {2014}, pages = {12-17}, author = {Kleesiek, J. and A. Biller and Urban, G. and Ullrich K{\"o}the and M. Bendszus and Fred A. Hamprecht} } @conference {kandemir_14_instance, title = {Instance Label Prediction by Dirichlet Process Multiple Instance Learning}, booktitle = {UAI. Proceedings}, year = {2014}, note = {1}, author = {Kandemir, M. and Fred A. Hamprecht} } @conference {urban_14_multi-modal, title = {Multi-modal Brain Tumor Segmentation using Deep Convolutional NeuralNetworks}, booktitle = {MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, winningcontribution}, year = {2014}, pages = {31-35}, author = {Urban, G. and M. Bendszus and Fred A. Hamprecht and Kleesiek, J.} } @conference {straehle_14_multiple, title = {Multiple instance learning with response-optimized random forests}, booktitle = {ICPR. Proceedings}, year = {2014}, note = {1}, pages = {3768 - 3773}, doi = {10.1109/ICPR.2014.647}, author = {Christoph N. Straehle and Kandemir, M. and Ullrich K{\"o}the and Fred A. Hamprecht} } @conference {yarkony_14_parallel, title = {Parallel Multicut Segmentation via Dual Decomposition}, booktitle = {New Frontiers in Mining Complex Patterns - Third International Workshop, {NFMCP} 2014, Held in Conjunction with {ECML-PKDD} 2014, Nancy, France, September 19, 2014, Revised Selected Papers}, year = {2014}, doi = {10.1007/978-3-319-17876-9_4}, url = {http://dx.doi.org/10.1007/978-3-319-17876-9_4}, author = {Julian Yarkony and Thorsten Beier and Pierre Baldi and Fred A. Hamprecht} } @article {maco_14_semiautomated, title = {Semiautomated Correlative 3D Electron Microscopy of In Vivo Imaged Axons and Dendrites}, journal = {Nature Protocols}, volume = {9}, year = {2014}, pages = {1354-1366}, doi = {10.1038/nprot.2014.101}, author = {Maco, B. and Cantoni, M. and Holtmaat, A. and Anna Kreshuk and Fred A. Hamprecht and G. W. Knott} } @conference {drory_14_semi-global, title = {Semi-Global Matching: A Principled Derivation in Terms of Message Passing}, booktitle = {GCPR. Proceedings}, number = {8753}, year = {2014}, note = {1}, pages = {43-53}, doi = {10.1007/978-3-319-11752-2_4}, author = {Drory, A. and Haubold, C. and Avidan, S. and Fred A. Hamprecht} } @article {koethe_14_simplestorm, title = {SimpleSTORM: a fast, self-calibrating reconstruction algorithm for localization microscopy}, journal = {Histochemistry and Cell Biology}, volume = {141}, year = {2014}, note = {1}, pages = {613-627}, doi = {10.1007/s00418-014-1211-4}, author = {Ullrich K{\"o}the and Herrmannsd{\"o}rfer, F. and Kats, I. and Fred A. Hamprecht} } @conference {diego_14_sparse, title = {Sparse Space-Time Deconvolution for Calcium Image Analysis}, booktitle = {NIPS. Proceedings}, year = {2014}, note = {1}, pages = {64-72}, url = {http://papers.nips.cc/paper/5342-sparse-space-time-deconvolution-for-calcium-image-analysis}, author = {Ferran Diego and Fred A. Hamprecht} } @incollection {lou_14_structured, title = {Structured Learning from Cheap Data}, year = {2014}, note = {1}, publisher = {The MIT Press}, author = {Lou, X. and Kloft, M. and R{\"a}tsch, G. and Fred A. Hamprecht}, editor = {Nowozin, S. et al} } @conference {fiaschi_14_tracking, title = {Tracking indistinguishable translucent objects over time using weakly supervised structured learning}, booktitle = {CVPR. Proceedings}, year = {2014}, note = {1}, pages = {2736 - 2743}, doi = {10.1109/CVPR.2014.356}, author = {Fiaschi, L. and Ferran Diego and Karl-Heinz Grosser and Schiegg, M. and Ullrich K{\"o}the and Zlatic, M. and Fred A. Hamprecht} } @conference {zhang_14_yeast, title = {Yeast Cell Detection and Segmentation in Bright Field Microscopy}, booktitle = {ISBI. Proceedings}, year = {2014}, note = {1}, pages = {1267-1270}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, doi = {10.1109/ISBI.2014.6868107}, author = {Zhang, C. and Huber, F. and Knop, M. and Fred A. Hamprecht} } @article {diego_13_automated, title = {Automated Identification of Neuronal Activity from Calcium Imaging by Sparse Dictionary Learning}, journal = {ISBI 2013. Proceedings}, number = {0236}, year = {2013}, note = {1}, pages = {1058-1061}, doi = {10.1109/ISBI.2013.6556660}, author = {Ferran Diego and Reichinnek, S. and M. Both and Fred A. Hamprecht} } @article {mikut_13_automated, title = {Automated Processing of Zebrafish Imaging Data: A Survey}, journal = {Zebrafish}, volume = {10 (3)}, year = {2013}, doi = {10.1089/zeb.2013.0886}, author = {Mikut, R. and Dickmeis, T. and Driever, W. and Geurts, P. and Fred A. Hamprecht and Bernhard X. Kausler and Ledesma-Carbayo, M. and Marée, R. and Mikula, K. and Pantazis, P. and Ronneberger, O. and Santos, A. and Stotzka, R.} } @conference {kappes_13_comparative, title = {A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems}, booktitle = {CVPR 2013. Proceedings}, year = {2013}, note = {1}, doi = {10.1109/CVPR.2013.175}, author = {J{\"o}rg H. Kappes and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, S. and Dhruv Batra and Sungwoong, K. and Bernhard X. Kausler and Lellmann, J. and Komodakis, N. and Carsten Rother} } @conference {Kappes-2013-benchmark, title = {A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problem}, booktitle = {CVPR}, year = {2013}, author = {J{\"o}rg H. Kappes and Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph Schn{\"o}rr and Nowozin, Sebastian and Dhruv Batra and Kim, Sungwoong and Bernhard X. Kausler and Lellmann, Jan and Komodakis, Nikos and Carsten Rother} } @conference {schiegg_13_conservation, title = {Conservation Tracking}, booktitle = {ICCV 2013. Proceedings}, year = {2013}, note = {1}, pages = {2928--2935}, doi = {10.1109/ICCV.2013.364}, author = {Schiegg, M. and Hanslovsky, P. and Bernhard X. Kausler and Hufnagel, L. and Fred A. Hamprecht} } @article {maco_13_correlative, title = {Correlative in vivo 2 photon and focused ion beam scanning electron microscopy of cortical neurons}, journal = {PloS one}, volume = {8 (2)}, year = {2013}, doi = {10.1371/journal.pone.0057405}, author = {Maco, B. and Holtmaat, A. and Cantoni, M. and Anna Kreshuk and Christoph N. Straehle and Fred A. Hamprecht and G. W. Knott} } @article {fiaschi_13_keeping, title = {Keeping Count: Leveraging Temporal Context to Count Heavily Overlapping Objects}, journal = {ISBI 2013.Proceedings}, year = {2013}, note = {1}, pages = {656-659}, doi = {10.1109/ISBI.2013.6556560}, author = {Fiaschi, L. and Karl-Heinz Grosser and Afonso, B. and Zlatic, M. and Fred A. Hamprecht} } @conference {straehle_13_ksmallest, title = {K-smallest Spanning Tree Segmentations}, booktitle = {German Conference on Pattern Recognition (DAGM/GCPR). Proceedings}, number = {8142}, year = {2013}, note = {1}, pages = {375-384}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-642-40602-7_40}, author = {Christoph N. Straehle and Peter, S. and Ullrich K{\"o}the and Fred A. Hamprecht} } @conference {diego_13_learning2, title = {Learning Multi-Level Sparse Representation}, booktitle = {NIPS. Proceedings}, year = {2013}, note = {1}, url = {http://papers.nips.cc/paper/5076-learning-multi-level-sparse-representations}, author = {Ferran Diego and Fred A. Hamprecht} } @conference {diego_13_learning, title = {Learning Multi-Level Sparse Representation for Identifying Neuronal Activity}, booktitle = {Signal Processing with Adaptive Sparse Structured Representations Workshop (SPARS). Book of Abstracts.}, year = {2013}, note = {1}, author = {Ferran Diego and Fred A. Hamprecht} } @conference {kroeger_13_learning, title = {Learning to Segment Neurons with Non-local Quality Measures}, booktitle = {MICCAI 2013. Proceedings, part II}, volume = {8150}, year = {2013}, note = {1}, pages = {419-427}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-642-40763-5_52}, author = {Thorben Kr{\"o}ger and Mikula, S. and Denk, W. and Ullrich K{\"o}the and Fred A. Hamprecht} } @conference {straehle_13_weakly, title = {Weakly supervised learning of image partitioning using decision trees with structured split criteria}, booktitle = {ICCV 2013. Proceedings}, year = {2013}, note = {1}, pages = {1849-1856}, doi = {10.1109/ICCV.2013.232}, author = {Christoph N. Straehle and Ullrich K{\"o}the and Fred A. Hamprecht} } @article {andres_11_3d, title = {3D Segmentation of SBFSEM Images of Neuropil by a Graphical Model over Supervoxel Boundaries}, journal = {Medical Image Analysis}, volume = {16 (2012)}, year = {2012}, note = {1}, pages = {796-805}, doi = {10.1016/j.media.2011.11.004}, author = {Bj{\"o}rn Andres and Ullrich K{\"o}the and Thorben Kr{\"o}ger and Helmstaedter, M. and K. L. Briggmann and Denk, W. and Fred A. Hamprecht} } @article {hanselmann_12_active, title = {Active Learning for Convenient Annotation and Classification of Secondary Ion Mass Spectrometry Images}, journal = {Analytical Chemistry}, volume = {85 (1)}, year = {2012}, note = {1}, pages = {147-155}, doi = {10.1021/ac3023313}, author = {Hanselmann, M. and R{\"o}der, J. and Ullrich K{\"o}the and B. Y. Renard and Heeren, R. M. A. and Fred A. Hamprecht} } @article {roeder_12_active, title = {Active Learning with Distributional Estimates}, journal = {UAI 2012. Proceedings}, year = {2012}, note = {1}, pages = {715-725}, author = {R{\"o}der, J. and Kunzmann, K. and Nadler, B. and Fred A. Hamprecht} } @article {zechmann_12_automated, title = {Automated vs. manual pattern recognition of 3D 1H MRSI data of patients with prostate cancer}, journal = {Academic Radiology}, volume = {19, 6}, year = {2012}, pages = {675-684}, doi = {10.1016/j.acra.2012.02.014}, author = {C. M. Zechmann and Bjoern H. Menze and B. Michael Kelm and Zamecnik, P. and Ikinger, U. and Waldherr, R. and Delorme, S. and Fred A. Hamprecht and Bachert, P.} } @conference {kausler_12_discrete, title = {A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness}, booktitle = {ECCV 2012. Proceedings}, volume = {7574}, year = {2012}, note = {1}, pages = {144-157}, doi = {10.1007/978-3-642-33712-3_11}, author = {Bernhard X. Kausler and Schiegg, M. and Bj{\"o}rn Andres and Lindner, M. and Ullrich K{\"o}the and Leitte, H. and Wittbrodt, J. and Hufnagel, L. and Fred A. Hamprecht} } @article {funke_12_efficient, title = {Efficient Automatic 3D-Reconstruction of Branching Neurons from EM Data}, journal = {CVPR 2012. Proceedings}, year = {2012}, note = {1}, pages = {1004-1011}, doi = {10.1109/CVPR.2012.6247777}, author = {Funke, J. and Bj{\"o}rn Andres and Fred A. Hamprecht and A. Cardona and Cook, M.} } @conference {andres_12_globally, title = {Globally Optimal Closed-Surface Segmentation for Connectomics}, booktitle = {ECCV 2012. Proceedings, Part 3}, number = {7574}, year = {2012}, note = {1}, pages = {778-791}, doi = {10.1007/978-3-642-33712-3_56}, author = {Bj{\"o}rn Andres and Thorben Kr{\"o}ger and K. L. Briggmann and Denk, W. and Norogod, N. and G. W. Knott and Ullrich K{\"o}the and Fred A. Hamprecht} } @conference {andres_12_lazy, title = {The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models}, booktitle = {Computer Vision - {ECCV} 2012 - 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part {VII}}, year = {2012}, doi = {10.1007/978-3-642-33786-4_12}, url = {http://dx.doi.org/10.1007/978-3-642-33786-4_12}, author = {Bj{\"o}rn Andres and J{\"o}rg H. Kappes and Thorsten Beier and Ullrich K{\"o}the and Fred A. Hamprecht} } @conference {Andres12, title = {The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models}, booktitle = {ECCV 2012}, year = {2012}, author = {Bj{\"o}rn Andres and J{\"o}rg H. Kappes and Thorsten Beier and Ullrich K{\"o}the and Fred A. Hamprecht} } @conference {Andres12, title = {The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models}, booktitle = {ECCV 2012}, year = {2012}, author = {Bj{\"o}rn Andres and J{\"o}rg Hendrik Kappes and Thorsten Beier and Ullrich K{\"o}the and Fred A. Hamprecht} } @article {fiaschi_12_learning, title = {Learning to Count with Regression Forest and Structured Labels}, journal = {ICPR 2012. Proceedings}, year = {2012}, note = {1}, pages = {2685-2688}, author = {Fiaschi, L. and Nair, R. and Ullrich K{\"o}the and Fred A. Hamprecht} } @article {lou_12_learning, title = {Learning to Segment Dense Cell Nuclei with Shape Prior}, journal = {CVPR 2012. Proceedings}, number = {0213}, year = {2012}, note = {1}, pages = {1012-1018}, doi = {10.1109/CVPR.2012.6247778}, author = {Lou, X. and Fred A. Hamprecht} } @article {sommer_12_learning-based, title = {Learning-based Mitotic Cell Detection in Histopathological Images}, journal = {ICPR 2012. Proceedings}, year = {2012}, note = {1}, pages = {2306-2309}, author = {Christoph Sommer and Fiaschi, L. and Fred A. Hamprecht and Gerlich, D.} } @article {horvat_12_one, title = {One plus one makes three (for social networks)}, journal = {PLoS ONE}, volume = {4,7}, year = {2012}, doi = {10.1371/journal.pone.0034740}, author = {Horvát, E.-Á. and Hanselmann, M. and Fred A. Hamprecht and K. A. Zweig} } @article {renard_12_overcoming, title = {Overcoming species boundaries in peptide identification with BICEPS}, journal = {Molecular and Cellular Proteomics}, volume = {11}, year = {2012}, doi = {10.1074/mcp.M111.014167}, author = {B. Y. Renard and Xu, B. and Kirchner, M. and Zickmann, F. and Winter, D. and Korten, S. and Brattig, N. and Tzur, A. and Fred A. Hamprecht and Steen, H.} } @article {lou_12_quality, title = {Quality Classification of Microscopic Imagery with Weakly Supervised Learning}, journal = {MICCAI-MLMI. Proceedings}, year = {2012}, note = {1}, pages = {176-183}, doi = {10.1007/978-3-642-35428-1_22}, author = {Lou, X. and Fiaschi, L. and Ullrich K{\"o}the and Fred A. Hamprecht} } @conference {straehle_12_seeded, title = {Seeded watershed cut uncertainty estimators for guided interactive segmentation}, booktitle = {CVPR 2012. Proceedings}, year = {2012}, note = {1}, pages = {765 - 772}, doi = {10.1109/CVPR.2012.6247747}, author = {Christoph N. Straehle and Ullrich K{\"o}the and Briggman, K. and Denk, W. and Fred A. Hamprecht} } @article {lou_12_structured, title = {Structured Learning from Partial Annotations}, journal = {ICML 2012. Proceedings}, year = {2012}, note = {1}, url = {http://icml.cc/discuss/2012/753.html}, author = {Lou, X. and Fred A. Hamprecht} } @article {horvat_12_you, title = {You Are Who Knows You: Predicting Links Between Non-Members of Facebook}, journal = {European Conference on Complex Systems. Proceedings}, volume = {3}, year = {2012}, note = {1}, pages = {309-315}, doi = {10.1007/978-3-319-00395-5_41}, author = {Horvát, E.-Á. and Hanselmann, M. and Fred A. Hamprecht and K. A. Zweig} } @article {kreshuk_11_automated2, title = {Automated Detection and Segmentation of Synaptic Contacts in Nearly Isotropic Serial Electron Microscopy Images}, journal = {PLoS ONE}, volume = {6 (10)}, year = {2011}, doi = {10.1371/journal.pone.0024899}, author = {Anna Kreshuk and Christoph N. Straehle and Christoph Sommer and Ullrich K{\"o}the and Cantoni, M. and G. W. Knott and Fred A. Hamprecht} } @conference {kreshuk_11_automated, title = {Automated Segmentation of Synapses in 3D EM Data}, booktitle = {Eighth IEEE International Symposium on Biomedical Imaging (ISBI 2011). Proceedings}, year = {2011}, note = {1}, pages = {220-223}, doi = {10.1109/ISBI.2011.5872392}, author = {Anna Kreshuk and Christoph N. Straehle and Christoph Sommer and Ullrich K{\"o}the and G. W. Knott and Fred A. Hamprecht} } @conference {straehle_11_carving, title = {Carving: Scalable Interactive Segmentation of Neural Volume Electron Microscopy Images}, booktitle = {MICCAI 2011, Proceedings.}, volume = {6891}, year = {2011}, note = {1}, pages = {653-660}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-642-23623-5_82}, author = {Christoph N. Straehle and Ullrich K{\"o}the and G. W. Knott and Fred A. Hamprecht} } @conference {kaster_11_comparative, title = {Comparative Validation of Graphical Models for Learning Tumor Segmentations from Noisy Manual Annotations}, booktitle = {LNCS}, volume = {LNCS 6533}, year = {2011}, note = {1}, pages = {74-85}, publisher = {Springer, Heidelberg}, organization = {Springer, Heidelberg}, doi = {10.1007/978-3-642-18421-5_8}, author = {F. O. Kaster and M.-A. Weber and Fred A. Hamprecht}, editor = {Bjoern H. Menze and Bjoern H. Menze and Langs, G. and Criminisi, A. and Tu, Z.} } @conference {lou_11_deltr, title = {DELTR: Digital Embryo Lineage Tree Reconstructor}, booktitle = {Eighth IEEE International Symposium on Biomedical Imaging (ISBI). Proceedings}, year = {2011}, note = {1}, pages = {1557-1560}, doi = {10.1109/ISBI.2011.5872698}, author = {Lou, X. and F. O. Kaster and Lindner, M. and Bernhard X. Kausler and Ullrich K{\"o}the and H{\"o}ckendorf, B. and Wittbrodt, J. and J{\"a}nicke, H. and Fred A. Hamprecht} } @conference {wanner_11_framework, title = {A Framework for Interactive Visualization and Classification of Dynamical Processes at the Water Surface}, booktitle = {16th International Workshop on Vision, Modelling and Visualization}, year = {2011}, note = {1}, pages = {199-206}, publisher = {Eurographics Association, Germany}, organization = {Eurographics Association, Germany}, doi = {10.2312/PE/VMV/VMV11/199-206}, author = {Sven Wanner and Christoph Sommer and Roland Rocholz and Fred A. Hamprecht and Bernd J{\"a}hne}, editor = {Eisert, P. and Joachim Hornegger and Konrad Polthier} } @conference {wanner2011, title = {A framework for interactive visualization and classification of dynamical processes at the water surface}, booktitle = {16th International Workshop on Vision, Modelling and Visualization}, year = {2011}, pages = {199--206}, publisher = {Eurographics Association, Germany}, organization = {Eurographics Association, Germany}, doi = {10.2312/PE/VMV/VMV11/199-206}, author = {Sven Wanner and Christoph Sommer and Roland Rocholz and Jung, M. and Fred A. Hamprecht and Bernd J{\"a}hne}, editor = {Peter Eisert and Joachim Hornegger and Konrad Polthier} } @article {roeder_11_gaussian, title = {Gaussian process classification: singly versus doubly stochastic models, and new computational schemes}, journal = {Stochastic Environmental Research \& Risk Assessment}, volume = {25 (7)}, year = {2011}, note = {1}, pages = {865-879}, doi = {10.1007/s00477-011-0498-0}, author = {R{\"o}der, J. and Tolosana-Delgado, R. and Fred A. Hamprecht} } @conference {sommer_11_ilastik, title = {ilastik: Interactive Learning and Segmentation Toolkit}, booktitle = {Eighth IEEE International Symposium on Biomedical Imaging (ISBI 2011).Proceedings}, year = {2011}, note = {1}, pages = {230-233}, doi = {10.1109/ISBI.2011.5872394}, author = {Christoph Sommer and Christoph N. Straehle and Ullrich K{\"o}the and Fred A. Hamprecht} } @article {frank_11_image-based, title = {Image-Based Supervision of a Periodically Working Machine}, journal = {Pattern Analysis and Applications}, year = {2011}, note = {1}, pages = {1-10}, doi = {10.1007/s10044-011-0245-7}, author = {Mario Frank and Fred A. Hamprecht} } @article {kaster_11_object-oriented, title = {An object-oriented library for systematic training and comparison of classifiers for computer-assisted tumor diagnosis from MRSI measurements}, journal = {Computer Science - Research and Development}, volume = {26}, year = {2011}, note = {1}, pages = {65-85}, doi = {10.1007/s00450-010-0143-z}, author = {F. O. Kaster and Merkel, B. and Nix, O. and Fred A. Hamprecht} } @conference {menze_11_on, title = {On oblique random forests}, booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2011. Proceedings.}, year = {2011}, note = {1}, pages = {453-469}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-642-23783-6_29}, author = {Bjoern H. Menze and B. Michael Kelm and Splitthoff, N. and Ullrich K{\"o}the and Fred A. Hamprecht} } @conference {andres_11_probabilistic, title = {Probabilistic Image Segmentation with Closedness Constraints}, booktitle = {ICCV, Proceedings}, year = {2011}, note = {1}, pages = {2611 - 2618}, doi = {10.1109/ICCV.2011.6126550}, author = {Bj{\"o}rn Andres and J{\"o}rg H. Kappes and Thorsten Beier and Ullrich K{\"o}the and Fred A. Hamprecht} } @conference {Andres11, title = {Probabilistic Image Segmentation with Closedness Constraints}, booktitle = {Proceedings of ICCV}, year = {2011}, author = {Bj{\"o}rn Andres and J{\"o}rg H. Kappes and Thorsten Beier and Ullrich K{\"o}the and Fred A. Hamprecht} } @conference {Andres11, title = {Probabilistic Image Segmentation with Closedness Constraints}, booktitle = {Proceedings of ICCV}, year = {2011}, author = {Bj{\"o}rn Andres and J{\"o}rg H. Kappes and Thorsten Beier and Ullrich K{\"o}the and Fred A. Hamprecht} } @article {hanselmann_11_sima, title = {SIMA: Simultaneous Multiple Alignment of LC/MS Peak Lists}, journal = {Bioinformatics}, volume = {27 (7)}, year = {2011}, note = {1}, pages = {987-993}, doi = {10.1093/bioinformatics/btr051}, author = {Hanselmann, M. and Bj{\"o}rn Voss and B. Y. Renard and Lindner, M. and Ullrich K{\"o}the and Kirchner, M. and Fred A. Hamprecht} } @conference {lou_11_structured, title = {Structured Learning for Cell Tracking}, booktitle = {NIPS 2011. Proceedings}, year = {2011}, note = {1}, pages = {1296-1304}, author = {Lou, X. and Fred A. Hamprecht}, editor = {Shawe-Taylor, J. and Zemel, R.S. and Pereira, F.C.N. and Weinberger, K.Q. and Bartlett, P.} } @article {kelm_11_using, title = {Using Spatial Prior Knowledge in the Spectral Fitting of Magnetic Resonance Spectroscopic Images}, journal = {NMR in Biomedicine}, volume = {25(1)}, year = {2011}, note = {1}, pages = {1-13}, doi = {10.1002/nbm.1704}, author = {B. Michael Kelm and F. O. Kaster and Henning, A. and M.-A. Weber and Bachert, P. and B{\"o}singer, P. and Fred A. Hamprecht and Bjoern H. Menze} } @article {pfannmoeller_11_visualizing, title = {Visualizing a homogeneous blend in bulk heterojunction polymer solar cells by analytical electron microscopy}, journal = {Nano Letters}, volume = {11}, year = {2011}, pages = {3099-3107}, doi = {10.1021/nl201078t}, author = {Pfannm{\"o}ller, M. and Fl{\"u}gge, H. and Benner, G. and Wacker, I. and Christoph Sommer and Hanselmann, M. and Schmale, S. and Schmidt, H. and Fred A. Hamprecht and Rabe, T. and Kowalsky, W. and Schr{\"o}der, R.} } @article {kreshuk_10_automated, title = {Automated detection and analysis of bimodal isotope peak distribution in H/D exchange mass spectrometry using HeXicon}, journal = {International Journal of Mass Spectrometry}, volume = {302}, year = {2010}, note = {1}, pages = {125-131}, doi = {10.1016/j.ijms.2010.08.025}, author = {Anna Kreshuk and Stankiewicz, M. and Lou, X. and Kirchner, M. and Fred A. Hamprecht and Mayer, M. P.} } @article {kirchner_10_computational, title = {Computational Protein Profile Similarity Screening for Quantitative Mass Spectrometry Experiments}, journal = {Bioinformatics}, volume = {26 (1)}, year = {2010}, note = {1}, pages = {77-83}, doi = {10.1093/bioinformatics/btp607}, author = {Kirchner, M. and B. Y. Renard and Ullrich K{\"o}the and Pappin, D. J. and Fred A. Hamprecht and Judith A. J. Steen and Steen, H.} } @article {lou_10_deuteration, title = {Deuteration Distribution Estimation with Improved Sequence Coverage for HX/MS Experiments}, journal = {Bioinformatics}, volume = {26(12)}, year = {2010}, note = {1}, pages = {1535-1541}, doi = {10.1093/bioinformatics/btq165}, author = {Lou, X. and Kirchner, M. and B. Y. Renard and Ullrich K{\"o}the and Graf, C. and Lee, C. and Judith A. J. Steen and Steen, H. and Mayer, M. P. and Fred A. Hamprecht} } @conference {andres_10_empirical, title = {An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM}, booktitle = {Pattern Recognition, Proc.~32th DAGM Symposium}, number = {6376}, year = {2010}, note = {1}, pages = {353-362}, doi = {10.1007/978-3-642-15986-2_36}, author = {Bj{\"o}rn Andres and J{\"o}rg H. Kappes and Ullrich K{\"o}the and Christoph Schn{\"o}rr and Fred A. Hamprecht} } @conference {Kappes-DAGM2010, title = {An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM}, booktitle = {Pattern Recognition, Proc.~32th DAGM Symposium}, year = {2010}, author = {Bj{\"o}rn Andres and J{\"o}rg H. Kappes and Ullrich K{\"o}the and Christoph Schn{\"o}rr and Fred A. Hamprecht} } @article {renard_10_estimating, title = {Estimating the Confidence of Peptide Identifications without Decoy Databases}, journal = {Analytical Chemistry}, year = {2010}, note = {1}, pages = {4314-4318}, doi = {10.1021/ac902892j}, author = {B. Y. Renard and Timm, W. and Kirchner, M. and Judith A. J. Steen and Fred A. Hamprecht and Steen, H.} } @conference {koethe_10_geometric, title = {Geometric Analysis of 3D Electron Microscopy Data}, booktitle = {Proceedings of Workshop on Discrete Geometry and Mathematical Morphology (WADGMM)}, year = {2010}, note = {1}, pages = {22-26}, author = {Ullrich K{\"o}the and Bj{\"o}rn Andres and Thorben Kr{\"o}ger and Fred A. Hamprecht}, editor = {Ullrich K{\"o}the and Montanvert, A. and Soille, P.} } @article {andres_10_how, title = {How to Extract the Geometry and Topology from Very Large 3D Segmentations}, journal = {ArXiv e-prints}, year = {2010}, note = {1}, url = {http://arxiv.org/abs/1009.6215}, author = {Bj{\"o}rn Andres and Ullrich K{\"o}the and Thorben Kr{\"o}ger and Fred A. Hamprecht} } @article {andres_10_lazy, title = {The Lazy Flipper: MAP Inference in Higher-Order Graphical Models by Depth-limited Exhaustive Search}, journal = {ArXiv e-prints}, year = {2010}, note = {1}, url = {http://arxiv.org/abs/1009.4102}, author = {Bj{\"o}rn Andres and J{\"o}rg H. Kappes and Ullrich K{\"o}the and Fred A. Hamprecht} } @article {kirchner_10_mgfp, title = {MGFp: An Open Mascot Generic Format Parser Library Implementation}, journal = {Journal of Proteome Research}, volume = {9 (5)}, year = {2010}, pages = {27622763}, doi = {10.1021/pr100118f}, author = {Kirchner, M. and Judith A. J. Steen and Fred A. Hamprecht and Steen, H.} } @article {menze_11_multimodal, title = {Multimodal Medical Image Analysis: from Visualization to Disease Modeling}, journal = {Zeitschrift f{\"u}r Med. Physik}, volume = {1}, year = {2010}, pages = {1-2}, doi = {10.1016/j.zemedi.2010.12.002}, author = {Bjoern H. Menze and Fred A. Hamprecht} } @conference {kaster_10_object-oriented, title = {An object-oriented library for systematic training and comparison of classifiers for computer-assisted tumor diagnosis from MRSI measurements}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2010 -- Algorithmen, Systeme, Anwendungen}, year = {2010}, note = {1}, pages = {97-101}, publisher = {Springer}, organization = {Springer}, author = {F. O. Kaster and Kassemeyer, S. and Merkel, B. and Nix, O. and Fred A. Hamprecht}, editor = {T. M. Deserno and H. Handels and T. Tolxdorff and Hans-Peter Meinzer} } @article {andres_10_runtime, title = {Runtime-Flexible Multi-dimensional Views and Arrays for C++98 and C++0x}, journal = {ArXiv e-prints}, year = {2010}, note = {1}, url = {http://arxiv.org/abs/1008.2909v1}, author = {Bj{\"o}rn Andres and Ullrich K{\"o}the and Thorben Kr{\"o}ger and Fred A. Hamprecht} } @article {goerlitz_09_allocation, title = {Allocation of particles to development processes}, journal = {Patent}, year = {2009}, author = {G{\"o}rlitz, L. and Fred A. Hamprecht and Staudacher, M.} } @article {hayn_09_analysing, title = {Analysing spatio-temporal patterns of the global NO2-distribution retrieved frome GOME satellite observations using a generalized additive model}, journal = {Atmospheric Chemistry and Physics}, volume = {9}, number = {17}, year = {2009}, note = {1}, pages = {9367-9398}, doi = {10.5194/acp-9-6459-2009}, author = {Hayn, M. and S. Beirle and Fred A. Hamprecht and Ulrich Platt and Bjoern H. Menze and T. Wagner} } @article {jaeger_09_analysis, title = {Analysis of Single-Molecule Fluorescence Spectroscopic Data with a Markov Modulated Poisson Process}, journal = {ChemPhysChem}, volume = {10:14}, year = {2009}, note = {1}, pages = {2486-2495}, doi = {10.1002/cphc.200900331}, author = {J{\"a}ger, M. and Kiel, A. and Herten, D.-P. and Fred A. Hamprecht} } @conference {kaster_09_classification, title = {Classification of Spectroscopic Images in the DIROlab Environment}, booktitle = {World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany}, volume = {25/V}, number = {25050252}, year = {2009}, pages = {252--255}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-642-03904-1_70}, author = {F. O. Kaster and B. Michael Kelm and C. M. Zechmann and M.-A. Weber and Fred A. Hamprecht and Nix, O.}, editor = {D{\"o}ssel, Olaf and Schlegel, Wolfgang C.} } @article {menze_09_comparison, title = {A Comparison of Random Forest and its Gini Importance with Standard Chemometric Methods for the Feature Selection and Classification of Spectral Data}, journal = {BMC Bioinformatics}, volume = {10:213}, year = {2009}, note = {1}, doi = {10.1186/1471-2105-10-213}, author = {Bjoern H. Menze and B. Michael Kelm and Masuch, R. and Himmelreich, U. and Bachert, P. and Petrich, W. and Fred A. Hamprecht} } @article {frank_09_denoising, title = {Denoising of Continuous-Wave Time-Of-Flight Depth Images Using Confidence Measures}, journal = {Optical Engineering}, volume = {48, 077003}, year = {2009}, note = {1}, doi = {10.1117/1.3159869}, author = {Mario Frank and Matthias Plaue and Fred A. Hamprecht} } @article {kelm_09_estimating, title = {Estimating Kinetic Parameter Maps from Dynamic Contrast-Enhanced MRI using Spatial Prior Knowledge}, journal = {IEEE Transaction on Medical Imaging}, volume = {28:10}, year = {2009}, note = {1}, pages = {1534-1547}, doi = {10.1109/TMI.2009.2019957}, author = {B. Michael Kelm and Bjoern H. Menze and Nix, O. and C. M. Zechmann and Fred A. Hamprecht} } @conference {hanselmann_09_multivariate, title = {Multivariate Watershed Segmentation of Compositional Data}, booktitle = {Proceedings of the 15th International Conference on Discrete Geometry for Computer Imagery (DGCI), in press}, volume = {5810}, year = {2009}, note = {1}, pages = {180-192}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-642-04397-0}, author = {Hanselmann, M. and Ullrich K{\"o}the and B. Y. Renard and Kirchner, M. and Heeren, R. M. A. and Fred A. Hamprecht} } @article {trittler_09_near-optimum, title = {Near-Optimum Sampling Design and an Efficient Algorithm for Single Tone Frequency Estimation}, journal = {Digital Signal Processing}, volume = {19}, year = {2009}, note = {1}, pages = {628-639}, doi = {10.1016/j.dsp.2008.10.003}, author = {Trittler, S. and Fred A. Hamprecht} } @article {goerlitz_09_processing, title = {Processing Spectral Data}, journal = {Surface and Interface Analysis}, volume = {41}, year = {2009}, note = {1}, pages = {636-644}, doi = {10.1002/sia.3066}, author = {G{\"o}rlitz, L. and Bjoern H. Menze and B. Michael Kelm and Fred A. Hamprecht} } @conference {andres_09_quantitative, title = {Quantitative Assessment of Image Segmentation Quality by Random Walk Relaxation Times}, booktitle = {Pattern Recognition. 31st DAGM Symposium, Jena, Germany, September 9-11, 2009. Proceedings}, volume = {5748}, year = {2009}, note = {1}, pages = {502-511}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-642-03798-6}, author = {Bj{\"o}rn Andres and Ullrich K{\"o}the and Bonea, A. and Nadler, B. and Fred A. Hamprecht} } @article {staudacher_09_selbstadaptivitaet, title = {Self Adjustment of Scanning Electron Microscopes / Selbstadaptivit{\"a}t von Rasterelektronenmikroskopen}, journal = {Patent, Patent Number WO2009062781A1}, year = {2009}, author = {Staudacher, M. and Fred A. Hamprecht and G{\"o}rlitz, L.} } @article {frank_09_theoretical, title = {Theoretical and Experimental Error Analysis of Continuous-Wave Time-Of-Flight Range Cameras}, journal = {Optical Engineering}, volume = {48, 013602}, year = {2009}, note = {1}, doi = {10.1117/1.3070634}, author = {Mario Frank and Matthias Plaue and Holger Rapp and Ullrich K{\"o}the and Bernd J{\"a}hne and Fred A. Hamprecht} } @article {frank2009, title = {Theoretical and experimental error analysis of continuous-wave time-of-flight range cameras}, journal = {Opt. Eng.}, volume = {48}, year = {2009}, pages = {013602}, abstract = {We offer a formal investigation of the measurement principle of time-of-flight 3-D cameras using correlation of amplitude-modulated continuous-wave signals. These sensors can provide both depth maps and IR intensity pictures simultaneously and in real time. We examine the theory of the data acquisition in detail. The variance of the range measurements is derived in a concise way and we show that the computed range follows an offset normal distribution. The impact of quantization of that distribution is discussed. All theoretically investigated errors like the behavior of the variance, depth bias, saturation and quantization effects are supported by experimental results.}, doi = {10.1117/1.3070634}, author = {Mario Frank and Matthias Plaue and Holger Rapp and Ullrich K{\"o}the and Bernd J{\"a}hne and Fred A. Hamprecht} } @article {hanselmann_09_towards, title = {Towards Digital Staining using Imaging Mass Spectrometry and Random Forests}, journal = {Journal of Proteome Research}, volume = {8}, year = {2009}, note = {1}, pages = {3558-3567}, doi = {10.1021/pr900253y}, author = {Hanselmann, M. and Ullrich K{\"o}the and Kirchner, M. and B. Y. Renard and Amstalden, E. R. and Glunde, K. and Heeren, R. M. A. and Fred A. Hamprecht} } @article {renard_09_when, title = {When Less Can Yield More - Computational Preprocessing of MS/MS Spectra for Peptide Identification Preprocessing}, journal = {Proteomics}, volume = {9}, year = {2009}, note = {1}, pages = {4978-4984}, doi = {10.1002/pmic.200900326}, author = {B. Y. Renard and Kirchner, M. and Monigatti, F. and Ivanov, A. R. and Rappsilber, J. and Winter, D. and Judith A. J. Steen and Fred A. Hamprecht and Steen, H.} } @article {hanselmann_08_concise, title = {Concise Representation of MS Images by Probabilistic Latent Semantic Analysis}, journal = {Analytical Chemistry}, volume = {80}, number = {24}, year = {2008}, note = {1}, pages = {9649-9658}, doi = {10.1021/ac801303x}, author = {Hanselmann, M. and Kirchner, M. and B. Y. Renard and Amstalden, E. R. and Glunde, K. and Heeren, R. M. A. and Fred A. Hamprecht} } @article {steen_08_different, title = {Different Phosphorylation States of the Anaphase Promoting Complex in Response to Anti-Mitotic Drugs: A Quantitative Proteomic Analysis}, journal = {Proceedings of the National Academy of Sciences}, volume = {105}, number = {16}, year = {2008}, note = {1}, pages = {6069-6074}, doi = {10.1073/pnas.0709807104}, author = {Judith A. J. Steen and Steen, H. and Georgi, A. and Kenneth C. Parker and Springer, M. and Kirchner, M. and Fred A. Hamprecht and Kirschner, M. W.} } @article {andres_08_errors-in-variables, title = {On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation}, journal = {Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on}, year = {2008}, note = {1}, pages = {1-6}, doi = {10.1109/CVPR.2008.4587571}, author = {Bj{\"o}rn Andres and Claudia Kondermann and Daniel Kondermann and Ullrich K{\"o}the and Fred A. Hamprecht and Christoph S. Garbe} } @conference {andres2008, title = {On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008}, year = {2008}, pages = {1--6}, publisher = {IEEE}, organization = {IEEE}, abstract = {Linear inverse problems in computer vision, including motion estimation, shape fitting and image reconstruction, give rise to parameter estimation problems with highly correlated errors in variables. Established total least squares methods estimate the most likely corrections Acirc and bcirc to a given data matrix [A, b] perturbed by additive Gaussian noise, such that there exists a solution y with [A + Acirc, b +bcirc]y = 0. In practice, regression imposes a more restrictive constraint namely the existence of a solution x with [A + Acirc]x = [b + bcirc]. In addition, more complicated correlations arise canonically from the use of linear filters. We, therefore, propose a maximum likelihood estimator for regression in the general case of arbitrary positive definite covariance matrices. We show that Acirc, bcirc and x can be found simultaneously by the unconstrained minimization of a multivariate polynomial which can, in principle, be carried out by means of a Grobner basis. Results for plane fitting and optical flow computation indicate the superiority of the proposed method.}, doi = {10.1109/CVPR.2008.4587571}, author = {Bj{\"o}rn Andres and Claudia Kondermann and Daniel Kondermann and Fred A. Hamprecht and Christoph S. Garbe} } @article {staudacher_08_method, title = {Method for processing an intensity image of a microscope}, journal = {Patent, Patent Number: WO2008034721A1}, year = {2008}, author = {Staudacher, M. and Fred A. Hamprecht and G{\"o}rlitz, L.} } @article {menze_08_mimicking, title = {Mimicking the human expert: pattern recognition for an automated assessment of data quality in MRSI}, journal = {Magnetic Resonance in Medicine}, volume = {59}, year = {2008}, note = {1}, pages = {1457-1466}, doi = {10.1002/mrm.21519}, author = {Bjoern H. Menze and B. Michael Kelm and M.-A. Weber and Bachert, P. and Fred A. Hamprecht} } @article {renard_08_nitpick, title = {NITPICK: Peak Identification for Mass Spectrometry Data}, journal = {BMC Bioinformatics}, volume = {9}, year = {2008}, pages = {355}, doi = {10.1186/1471-2105-9-355}, author = {B. Y. Renard and Kirchner, M. and Steen, H. and Judith A. J. Steen and Fred A. Hamprecht} } @article {jaeger_08_principal, title = {Principal Component Imagery for the Quality Monitoring of Dynamic Laser Welding Processes}, journal = {IEEE Transactions on Industrial Electronics}, volume = {56:4}, year = {2008}, pages = {1307-1313}, doi = {10.1109/TIE.2008.2008339}, author = {J{\"a}ger, M. and Fred A. Hamprecht} } @article {koenig_08_robust, title = {Robust Prediction of the MASCOT Score for an Improved Quality Assessment in Mass Spectrometric Proteomics}, journal = {Journal of Proteome Research}, volume = {7}, number = {9}, year = {2008}, note = {1}, pages = {3708-3717}, doi = {10.1021/pr700859x}, author = {K{\"o}nig, T. and Bjoern H. Menze and Kirchner, M. and Monigatti, F. and Kenneth C. Parker and Patterson, T. and Judith Jebanthirajah Steen and Fred A. Hamprecht and Steen, H.} } @conference {andres_08_segmentation, title = {Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification}, booktitle = {Pattern Recognition. 30th DAGM Symposium Munich, Germany, June 10-13, 2008. Proceedings}, volume = {5096}, year = {2008}, note = {1}, pages = {142-152}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-540-69321-5_15}, author = {Bj{\"o}rn Andres and Ullrich K{\"o}the and Helmstaedter, M. and Denk, W. and Fred A. Hamprecht}, editor = {Gerhard Rigoll} } @article {jaeger_08_sputter, title = {Sputter Tracking for the Automatic Monitoring of Industrial Laser Welding Processes}, journal = {IEEE Transactions on Industrial Electronics}, volume = {55}, number = {5}, year = {2008}, pages = {2177-2184}, doi = {10.1109/TIE.2008.918637}, author = {J{\"a}ger, M. and Humbert, S. and Fred A. Hamprecht} } @article {rapp_08_theoretical, title = {A Theoretical and Experimental Investigation of the Systematic Errors and Statistical Uncertainties of Time-of-Flight Cameras}, journal = {Int. J. Intelligent Systems Technologies and Applications}, volume = {5}, number = {3}, year = {2008}, note = {1}, pages = {402-413}, doi = {10.1504/IJISTA.2008.021303}, author = {Holger Rapp and Mario Frank and Fred A. Hamprecht and Bernd J{\"a}hne} } @article {rapp2008, title = {A theoretical and experimental investigation of the systematic errors and statistical uncertainties of time-of-flight cameras}, journal = {Int. J. Intelligent Systems Technologies and Applications}, volume = {5}, year = {2008}, pages = {402--413}, abstract = {The following paper presents a model to predict the systematic errors and statistical uncertainties of Time-Of-Flight (TOF) 3D imaging systems. The experimental data obtained with a custom build test setup show that the SD of the depth signal rises approximately quadratically with the depth. The most significant systematic depth error is periodic with an amplitude of around 50mm. It is provoked by the inharmonic correlation function. The inhomogeneity in each pixel (fixed pattern) accounts for a depth error of about 20mm, while illumination and reflectivity variations cause depth errors of less than 10mm, provided that no overflows occur.}, doi = {10.1504/IJISTA.2008.021303}, author = {Holger Rapp and Mario Frank and Fred A. Hamprecht and Bernd J{\"a}hne} } @article {jaeger_08_weakly, title = {Weakly Supervised Learning of a Classifier for Unusual Event Detection}, journal = {IEEE Transactions on Image Processing}, volume = {17}, number = {9}, year = {2008}, note = {1}, pages = {1700-1708}, doi = {10.1109/TIP.2008.2001043}, author = {J{\"a}ger, M. and Knoll, C. and Fred A. Hamprecht} } @conference {kondermann2007, title = {An adaptive confidence measure for optical flows based on linear subspace projections}, booktitle = {Proceedings of the 29th DAGM Symposium on Pattern Recognition}, volume = {4713}, year = {2007}, pages = {132--141}, publisher = {Springer}, organization = {Springer}, abstract = {Confidence measures are important for the validation of optical flow fields by estimating the correctness of each displacement vector. There are several frequently used confidence measures, which have been found of at best intermediate quality. Hence, we propose a new confidence measure based on linear subspace projections. The results are compared to the best previously proposed confidence measures with respect to an optimal confidence. Using the proposed measure we are able to improve previous results by up to 31\%.}, doi = {10.1007/978-3-540-74936-3_14}, author = {Claudia Kondermann and Daniel Kondermann and Bernd J{\"a}hne and Christoph S. Garbe and Christoph Schn{\"o}rr and Bernd J{\"a}hne}, editor = {Fred A. Hamprecht} } @article {kirchner_07_amsrpm, title = {amsrpm: Robust Point Matching in Retention Time Alignment of LC/MS Data with R}, journal = {Journal of Statistical Software}, volume = {18}, number = {4}, year = {2007}, note = {1}, pages = {1-12}, url = {http://www.jstatsoft.org/v18/i04/paper}, author = {Kirchner, M. and Saussen, B. and Steen, H. and Judith A. J. Steen and Fred A. Hamprecht} } @article {kelm_07_automated, title = {Automated Estimation of Tumor Probability in Prostate MRSI: Pattern Recognition vs. Quantification}, journal = {Magnetic Resonance in Medicine}, volume = {57}, number = {1}, year = {2007}, note = {1}, pages = {150-159}, doi = {10.1002/mrm.21112}, author = {B. Michael Kelm and Bjoern H. Menze and C. M. Zechmann and Baudendistel, K. T. and Fred A. Hamprecht} } @article {weber_07_comparison, title = {Comparison of correctness of manuel and automatic evaluation of MR-spectrum with prostrate cancer}, journal = {Der Urologe}, volume = {46}, number = {9}, year = {2007}, pages = {1252}, doi = {10.1007/s00120-007-1488-1}, author = {C. Weber and C. M. Zechmann and B. Michael Kelm and Zamecnik, R. and Hendricks, D. and Waldherr, R. and Fred A. Hamprecht and Delorme, S. and Bachert, P. and Ikinger, U.} } @conference {garbe2007, title = {Fluid flow estimation through integration of physical flow configurations}, booktitle = {Proceedings of the 29th DAGM Symposium on Pattern Recognition}, year = {2007}, pages = {92--101}, publisher = {Springer}, organization = {Springer}, abstract = {The measurement of fluid flows is an emerging field for optical flow computation. In a number of such applications, a tracer is visualized with modern digital cameras. Due to the projective nature of the imaging process, the tracer is integrated across a velocity profile. In this contribution, a novel technique is presented that explicitly models brightness changes due to this integration. Only through this modeling is an accurate estimation of the flow velocities feasible. Apart from an accurate measurement of the fluid flow, also the underlying velocity profile can be reconstructed. Applications from shear flow, microfluidics and a biological applications are presented.}, doi = {10.1007/978-3-540-74936-3_10}, author = {Christoph S. Garbe and Christoph Schn{\"o}rr and Bernd J{\"a}hne}, editor = {Fred A. Hamprecht} } @conference {menze_07_from, title = {From eigenspots to fisherspots -- latent spaces in the nonlinear detection of spot patterns in a highly variable background}, booktitle = {Advances in data analysis}, volume = {33}, year = {2007}, note = {1}, pages = {255-262}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-540-70981-7_29}, author = {Bjoern H. Menze and B. Michael Kelm and Fred A. Hamprecht}, editor = {Lenz, H.-J. and Decker, R.} } @article {schmaehling_07_generalizing, title = {Generalizing the Abbott-Firestone curve by two new surface descriptors}, journal = {Wear}, volume = {262}, year = {2007}, note = {1}, pages = {1360-1371}, doi = {10.1016/j.wear.2007.01.025}, author = {Schm{\"a}hling, J. and Fred A. Hamprecht} } @article {menze_07_multivariate, title = {Multivariate feature selection and hierarchical classification for infrared spectroscopy: serum-based detection of bovine spongiform encephalopathy}, journal = {Analytical and Bioanalytical Chemistry}, volume = {387}, number = {5}, year = {2007}, note = {1}, pages = {1801-1807}, doi = {10.1007/s00216-006-1070-5}, author = {Bjoern H. Menze and Petrich, W. and Fred A. Hamprecht} } @proceedings {DAGM07, title = {Pattern Recognition {\textendash} 29th DAGM Symposium}, volume = {4713}, year = {2007}, publisher = {Springer}, editor = {Fred A. Hamprecht and Christoph Schn{\"o}rr and Bernd J{\"a}hne} } @book {hamprecht_07_pattern, title = {Pattern Recognition, 29th DAGM Symposium, Heidelberg, Germany, September 12-14, 2007, Proceedings}, volume = {4713}, year = {2007}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-540-74936-3}, editor = {Fred A. Hamprecht and Bernd J{\"a}hne and Christoph Schn{\"o}rr} } @proceedings {hamprecht2007, title = {Pattern Recognition, 29th DAGM Symposium, Heidelberg, Germany, September 12-14}, volume = {4713}, year = {2007}, publisher = {Springer}, doi = {10.1007/978-3-540-74936-3}, author = {Christoph Schn{\"o}rr and Bernd J{\"a}hne}, editor = {Fred A. Hamprecht} } @conference {andres_07_selection, title = {Selection of Local Optical Flow Models by Means of Residual Analysis}, booktitle = {Pattern Recognition}, volume = {4713}, year = {2007}, note = {1}, pages = {72-81}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-540-74936-3_8}, author = {Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph S. Garbe}, editor = {Christoph Schn{\"o}rr and Bernd J{\"a}hne and Fred A. Hamprecht} } @conference {andres2007, title = {Selection of local optical flow models by means of residual analysis}, booktitle = {Proceedings of the 29th DAGM Symposium on Pattern Recognition}, year = {2007}, pages = {72--81}, publisher = {Springer}, organization = {Springer}, abstract = {This contribution presents a novel approach to the challenging problem of model selection in motion estimation from sequences of images. New light is cast on parametric models of local optical flow. These models give rise to parameter estimation problems with highly correlated errors in variables (EIV). Regression is hence performed by equilibrated total least squares. The authors suggest to adaptively select motion models by testing local empirical regression residuals to be in accordance with the probability distribution that is theoretically predicted by the EIV model. Motion estimation with residual-based model selection is examined on artificial sequences designed to test specifically for the properties of the model selection process. These simulations indicate a good performance in the exclusion of inappropriate models and yield promising results in model complexity control.}, doi = {10.1007/978-3-540-74936-3_8}, author = {Bj{\"o}rn Andres and Christoph S. Garbe and Christoph Schn{\"o}rr and Bernd J{\"a}hne}, editor = {Fred A. Hamprecht and Fred A. Hamprecht} } @conference {goerlitz_07_semi, title = {Semi-Supervised Tumor Detection in MRSI With Discriminative Random Fields}, booktitle = {Pattern Recognition}, volume = {4713}, year = {2007}, note = {1}, pages = {224-233}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/978-3-540-74936-3_23}, author = {G{\"o}rlitz, L. and Bjoern H. Menze and M.-A. Weber and B. Michael Kelm}, editor = {Fred A. Hamprecht and Fred A. Hamprecht and Christoph Schn{\"o}rr and Bernd J{\"a}hne} } @conference {rapp2007, title = {A theoretical and experimental investigation of the systematic errors and statistical uncertainties of time-of-flight cameras}, booktitle = {Proc.\ Dyn3D Workshop, Heidelberg, Sept. 11, 2007}, year = {2007}, publisher = {ZESS, Univ.\ Siegen}, organization = {ZESS, Univ.\ Siegen}, author = {Holger Rapp and Mario Frank and Fred A. Hamprecht and Bernd J{\"a}hne} } @conference {kelm_06_bayesian, title = {Bayesian Estimation of Smooth Parameter Maps for Dynamic Contrast-Enhanced MR Images with Block-ICM}, booktitle = {Proc Computer Vision and Pattern Recognition Workshop (Mathematical Methods in Biomedical Image Analysis)}, year = {2006}, note = {1}, pages = {96-103}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, doi = {10.1109/CVPRW.2006.41}, author = {B. Michael Kelm and M{\"u}ller, N. and Bjoern H. Menze and Fred A. Hamprecht}, editor = {Schmid, C. and Soatto, S. and Tomasi, C.} } @conference {zechmann_06_can, title = {Can man still beat the machine? Automated vs. manual pattern recognition of 3D MRSI data of prostate cancer patients}, booktitle = {Proceedings of the 16th ISMRM}, year = {2006}, author = {C. M. Zechmann and B. Michael Kelm and Zamecnik, P. and Ikinger, U. and Waldherr, R. and R{\"o}ll, S. and Delorme, S. and Fred A. Hamprecht and Bachert, P.} } @conference {kelm_06_claret, title = {CLARET: a tool for fully automated evaluation of MRSI with pattern recognition methods.}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2006 - Algorithmen, Systeme, Anwendungen}, year = {2006}, note = {1}, pages = {51-55}, publisher = {Springer}, organization = {Springer}, doi = {10.1007/3-540-32137-3_7}, url = {http://www.efmi-wg-mip.net/service/bvm2006}, author = {B. Michael Kelm and Bjoern H. Menze and Neff, T. and C. M. Zechmann and Fred A. Hamprecht}, editor = {H. Handels and G. Bebis and et al.} } @inbook {carlsohn_06_spectral, title = {Color image processing}, volume = {7(17)}, year = {2006}, pages = {393-419}, publisher = {CRC Press}, organization = {CRC Press}, chapter = {Spectral Imaging and Applications}, author = {Carlsohn, M. F. and Bjoern H. Menze and B. Michael Kelm and Fred A. Hamprecht and Kercek, A. and Leitner, R. and Polder, G.}, editor = {Lukac, R. and Plataniotis, K.N.} } @article {lichy_06_einsatz, title = {Einsatz der 1H-MR-spektroskopischen Bildgebung in der Strahlentherapie: Cholin als Marker f{\"u}r die Bestimmung der relativen Wahrscheinlichkeit eines Tumorprogresses nach Bestrahlung glialer Hirntumoren}, journal = {Zeitung f{\"u}r R{\"o}ntgenforschung}, volume = {178}, year = {2006}, pages = {627-633}, doi = {10.1055/s-2006-926744}, author = {M. P. Lichy and Bachert, P. and Fred A. Hamprecht and M.-A. Weber and Debus, J. and Schulz-Ertner, D. and Kauczor, H.-U. and Schlemmer, H.-P.} } @conference {menze_06_machine-based, title = {Machine-based rejection of low quality spectra and estimation of brain tumor probabilities from magnetic resonance spectroscopic images}, booktitle = {Bildverarbeitung f{\"u}r die Medizin}, year = {2006}, note = {1}, pages = {31-36}, doi = {10.1007/3-540-32137-3_7}, author = {Bjoern H. Menze and B. Michael Kelm and Heck, D. and M. P. Lichy and Fred A. Hamprecht}, editor = {H. Handels and G. Bebis and et al.} } @article {menze_06_optimal, title = {Optimal Classification of Long Echo Time in vivo Magnetic Resonance Spectra in the Detection of Recurrent Brain Tumor}, journal = {NMR in Biomedicine}, volume = {19}, number = {5}, year = {2006}, note = {1}, pages = {599-609}, doi = {10.1002/nbm.1041}, author = {Bjoern H. Menze and M. P. Lichy and Bachert, P. and B. Michael Kelm and Schlemmer, H. P. and Fred A. Hamprecht} } @article {sieg_06_qcar, title = {A QCAR-approach to materials modelling}, journal = {Journal of Molecular Modeling}, volume = {12}, year = {2006}, note = {1}, pages = {611-619}, doi = {10.1007/s00894-005-0068-9}, author = {Sieg, S. and Stutz, B. and Schmidt, T. and Fred A. Hamprecht and Maier, W. F.} } @article {schmaehling_06_threedimensional, title = {A three-dimensional measure of surface roughness based on mathematical morphology}, journal = {International Journal of Machine Tools and Manufacture}, volume = {46 (14)}, year = {2006}, note = {1}, pages = {1764-1769}, doi = {10.1016/j.ijmachtools.2005.12.003}, author = {Schm{\"a}hling, J. and Fred A. Hamprecht and Hoffmann, D. M. P.} } @techreport {koenig_05_application, title = {On the Application of Multiscale Motion Estimation in Intravascular Elastography}, year = {2005}, institution = {University of Heidelberg}, author = {K{\"o}nig, T. and Fred A. Hamprecht and K{\"u}cherer, H.} } @conference {kelm_05_automatische, title = {Automatische Lokalisation von Tumoren in 1H-NMR-spektroskopischen in vivo Aufnahmen}, booktitle = {VDI-Berichte}, volume = {1883}, year = {2005}, note = {1}, pages = {457-466}, author = {B. Michael Kelm and Bjoern H. Menze and Fred A. Hamprecht} } @booklet {jaeger_05_automatisierte, title = {Automatisierte Klassifikation von Laserschwei\DFprozessen durch Nutzung von 3D Signalverarbeitungs-Algorithmen}, year = {2005}, publisher = {Robert Bosch GmbH, Schwieberdingen and IWR, Uni Heidelberg}, author = {J{\"a}ger, M. and Knoll, C. and Fred A. Hamprecht} } @article {hissmann_05_bayesian, title = {Bayesian surface estimation for white light interferometry}, journal = {Optical Engineering}, volume = {44}, year = {2005}, note = {1}, pages = {1-9}, doi = {10.1117/1.829651}, author = {Hissmann, M. and Fred A. Hamprecht} } @booklet {goerlitz_05_detektion, title = {Detektion von Partikeln in Intensit{\"a}tsbildern mit Hilfe eines morphologischen Skalenraumes}, year = {2005}, publisher = {Robert-Bosch GmbH, University of Heidelberg}, author = {G{\"o}rlitz, L. and Fred A. Hamprecht and Staudacher, M.} } @article {kuensch_05_optimal, title = {Optimal lattices for sampling}, journal = {IEEE Transactions on Information Theory}, volume = {51}, number = {0055}, year = {2005}, pages = {634-647}, doi = {10.1109/TIT.2004.840864}, author = {K{\"u}nsch, H. R. and Agrell, E. and Fred A. Hamprecht} } @conference {zhang_05_voc, title = {Report about VOCs Dataset{\textquoteright}s Analysis based on Random Forests}, booktitle = {Proceedings of the HPC-Asia05}, year = {2005}, pages = {603-607}, publisher = {IEEE Computer Society Press}, organization = {IEEE Computer Society Press}, author = {Zhang, H. and Fred A. Hamprecht and Amann, A.} } @incollection {hamprecht_04_classification, title = {Classification}, year = {2004}, pages = {509-519}, publisher = {CRC Press}, edition = {2nd}, author = {Fred A. Hamprecht}, editor = {Bernd J{\"a}hne} } @conference {menze_04_classification, title = {Classification of in vivo magnetic resonance spectra}, booktitle = {Classification in ubiquitous challenge: Proceedings of the GfKl 2004}, year = {2004}, pages = {362-369}, publisher = {Springer}, organization = {Springer}, author = {Bjoern H. Menze and Wormit, M. and Bachert, P. and M. P. Lichy and Schlemmer, H.-P. and Fred A. Hamprecht} } @article {restle_04_nonparametric, title = {Nonparametric Smoothing of Height maps using {\textquoteleft}{\textquoteleft}Confidence{\textquoteright}{\textquoteright} values}, journal = {Optical Engineering}, volume = {43}, number = {0049}, year = {2004}, pages = {866-871}, doi = {10.1117/1.1666622}, author = {J. Restle and Hissmann, M. and Fred A. Hamprecht} } @incollection {hader_04_two-stage, title = {Two-Stage Classification with Automatic Feature Selection for an Industrial Application}, year = {2004}, pages = {137-144}, publisher = {Springer}, author = {S. Hader and Fred A. Hamprecht}, editor = {Weihs, C. and Gaul, W.} } @article {hamprecht_04_bild, title = {Vom Bild zur Information}, journal = {Ruperto Carola -- Forschungsmagazin der Universit{\"a}t Heidelberg}, volume = {03.2004}, number = {0051}, year = {2004}, pages = {9-12}, doi = {http://www.uni-heidelberg.de/presse/ruca/ruca04-03/s09bild.html}, author = {Fred A. Hamprecht and Bernd J{\"a}hne} } @booklet {hamprecht2004, title = {Vom Bild zur Information}, year = {2004}, author = {Fred A. Hamprecht and Bernd J{\"a}hne} } @conference {hissmann_03_bayessche, title = {Bayessche Sch{\"a}tzung von H{\"o}henkarten aus der Wei\DF licht-Interferometrie}, booktitle = {Oberfl{\"a}chenmesstechnik 2003}, year = {2003}, pages = {187--196}, author = {Hissmann, M. and Fred A. Hamprecht} } @incollection {hader_03_efficient, title = {Efficient Density Clustering}, year = {2003}, pages = {39-48}, publisher = {Springer}, doi = {10.1007/b13634}, author = {S. Hader and Fred A. Hamprecht}, editor = {Schader, M. and Gaul, W. and Vichi, M.} } @incollection {hamprecht_03_exploring, title = {Exploring a space of materials: spatial sampling design and subset selection}, year = {2003}, note = {1}, publisher = {Wiley}, chapter = {13}, author = {Fred A. Hamprecht and Agrell, E.}, editor = {Cawse, J. N.} } @incollection {eisele_03_approach, title = {A new approach for defect detection in X-ray CT images}, volume = {2449}, year = {2003}, pages = {345-352}, publisher = {Springer}, doi = {10.1007/3-540-45783-6}, author = {H. Eisele and Fred A. Hamprecht}, editor = {Luc Van Gool} } @article {hamprecht_02_chemical, title = {Chemical library subset selection algorithms: a unified derivation using spatial statistics}, journal = {Journal of Chemical Information and Computer Sciences}, volume = {42}, year = {2002}, pages = {414-428}, author = {Fred A. Hamprecht and Thiel, W. and van Gunsteren, W. F.} } @article {jaehne_02_anspruchsvolle, title = {F{\"u}r Anspruchsvolle - Multidimensionale Bildverarbeitung in der Produktion}, journal = {Qualit{\"a}t und Zuverl{\"a}ssigkeit}, volume = {47}, year = {2002}, pages = {1154-1159}, author = {Bernd J{\"a}hne and Martin Brocke and H. Eisele and S. Hader and Fred A. Hamprecht and W. Happold and Florian Raisch and J. Restle} } @article {gee_02_molecular, title = {A molecular dynamics simulation study of the conformational preferences of oligo-(3- hydroxyalcanoic acids) in chloroform solution}, journal = {Helv. Chim. Acta}, volume = {85}, year = {2002}, pages = {618-632}, author = {Gee, P. J. and Fred A. Hamprecht and Schuler, L. D. and van Gunsteren, W. F. and Duchardt, E. and Schwalbe, H. and Albert, M. and Seebach, D.} } @article {jaehne2002g, title = {Multidimensionale Bildverarbeitung in der Produktion}, journal = {QZ}, volume = {47}, year = {2002}, pages = {1154--1159}, url = {http://www.qz-online.de/qz-zeitschrift/archiv/artikel/multidimensionale-bildverarbeitung-in-der-produktion-fuer-anspruchsvolle-338129.html}, author = {Bernd J{\"a}hne and Martin Brocke and H. Eisele and S. Hader and Fred A. Hamprecht and W. Happold and Florian Raisch and J. Restle} } @article {hamprecht_01_fibrillation, title = {Fibrillation power: An alternative method of ECG spectral analysis for prediction of countershock success in a porcine model of ventricular fibrillation}, journal = {Resuscitation}, volume = {50}, year = {2001}, pages = {287-296}, author = {Fred A. Hamprecht and Achleitner, U. and Krismer, A. C. and Lindner, K. H. and Wenzel, V. and Strohmenger, H.-U. and Thiel, W. and van Gunsteren, W. F.} } @article {hamprecht_01_preliminary, title = {Preliminary results on the prediction of countershock success with fibrillation power}, journal = {Resuscitation}, volume = {50}, year = {2001}, pages = {297-299}, author = {Fred A. Hamprecht and Jost, D. and R{\"u}ttimann, M. and Calamai, F. and Kowalski, J. J.} } @article {hamprecht_01_strategy, title = {A strategy for analysis of (molecular) equilibrium simulations: configuration space density estimation, clustering and visualization}, journal = {Journal of Chemical Physics}, volume = {114}, year = {2001}, pages = {2079-2089}, author = {Fred A. Hamprecht and Peter, C. and Daura, X. and Thiel, W. and van Gunsteren, W. F.} } @article {hamprecht_98_development, title = {Development and assessment of new exchange-correlation functionals}, journal = {Journal of Chemical Physics}, volume = {109}, year = {1998}, pages = {6264-6271}, doi = {10.1063/1.477267}, author = {Fred A. Hamprecht and Cohen, A. J. and Tozer, D. J. and Handy, N. C.} } @article {buehl_98_theoretical, title = {Theoretical Investigation of NMR Chemical Shifts and Reactivities of Oxovanadium (V) Compounds}, journal = {Journal of Computational Chemistry}, volume = {19}, year = {1998}, pages = {113-122}, author = {B{\"u}hl, M. and Fred A. Hamprecht} } @article {kubinyi_98_threedimensional, title = {Threedimensional Quantitative Similarity-Activity Relationships (3DQSiAR) from SEAL Similarity Matrices}, journal = {Journal of Medicinal Chemistry}, volume = {41}, year = {1998}, pages = {2553-2564}, author = {Kubinyi, H. and Fred A. Hamprecht and Mietzner, T.} } @article {hamprecht_97_generation, title = {Generation of pseudo-native protein structures for threading}, journal = {Proteins}, volume = {28}, year = {1997}, pages = {522-529}, author = {Fred A. Hamprecht and Scott, W. R. P. and van Gunsteren, W. F.} }