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 Vijayan, A, Tofanelli, R, Strauss, S, Cerrone, L, Wolny, A, Strohmeier, J, Kreshuk, A, Hamprecht, F A, Smith, R S and Schneitz, K (2021). A Digital 3D Reference Atlas Reveals Cellular Growth Patterns Shaping the Arabidopsis Ovule. eLife\par \par  Hehn, T M, Kooij, J F P and Hamprecht, F A (2020). End-to-End Learning of Decision Trees and Forests. International Journal of Computer Vision. 128 997-1011\par \par  Hau\'dfmann, M, Hamprecht, F A and Kandemir, M (2019). Deep Active Learning with Adaptive Acquisition. IJCAI. Proceedings. 2470-2476\par \par  Cerrone, L, Zeilmann, A and Hamprecht, F A (2019). End-to-End Learned Random Walker for Seeded Image Segmentation. CVPR. Proceedings. 12559-12568\par \par  Berg, S, Kutra, D, Kroeger, T, Straehle, C N, Kausler, B X, Haubold, C, Schiegg, M, Ales, J, Beier, T, Rudy, M, Eren, K, Cervantes, J I, Xu, B, Beuttenm\'fcller, F, Wolny, A, Zhang, C, K\'f6the, U, Hamprecht, F A and Kreshuk, A (2019). ilastik: interactive machine learning for (bio)image analysis. Nature Methods. 16 1226-1232\par \par  Kirschbaum, E, Hau\'dfmann, M, Wolf, S, Sonntag, H, Schneider, J, Elzoheiry, S, Kann, O, Durstewitz, D and Hamprecht, F A (2019). LeMoNADe: Learned Motif and Neuronal Assembly Detection in calcium imaging videos. ICLR. Proceedings\par \par  Hau\'dfmann, M, Hamprecht, F A and Kandemir, M (2019). Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation. UAI. Proceedings. 563-573\par \par  Hehn, T and Hamprecht, F A (2018). End-to-end Learning of Deterministic Decision Trees. German Conference on Pattern Recognition. Proceedings. Springer. LNCS 11269 612-627\par \par  Draxler, F, Veschgini, K, Salmhofer, M and Hamprecht, F A (2018). Essentially No Barriers in Neural Network Energy Landscape. ICML. Proceedings. 80 1308--1317\par \par  Weiler, M, Hamprecht, F A and Storath, M (2018). Learning Steerable Filters for Rotation Equivariant CNNs. CVPR. Proceedings. 849-858\par \par  Wolf, S, Pape, C, Bailoni, A, Rahaman, N, Kreshuk, A, K\'f6the, U and Hamprecht, F A (2018). The Mutex Watershed: Efficient, Parameter-Free Image Partitioning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 11208 LNCS 571?587. http://arxiv.org/abs/1904.12654\par \par  Wolf, S, Pape, C, Bailoni, A, Rahaman, N, Kreshuk, A, K\'f6the, U and Hamprecht, F A (2018). The Mutex Watershed: Efficient, Parameter-Free Image   Partitioning. ECCV. Proceedings. Springer. 571-587\par \par  Rahaman, N, Arpit, D, Baratin, A, Draxler, F, Lin, M, Hamprecht, F A, Bengio, Y and Courville, A (2018). On the spectral bias of deep neural networks. arXiv preprint arXiv:1806.08734\par \par  Kandemir, M, Hamprecht, F A, Wojek, C and Schmidt, U (2017). Active machine learning for training an event classification. Patent, Patent Number WO2017032775 A1\par \par  Peter, S, Diego, F, Hamprecht, F A and Nadler, B (2017). Cost-efficient Gradient Boosting. NIPS, poster\par \par  Haubold, C, Uhlmann, V, Unser, M and Hamprecht, F A (2017). Diverse M-best Solutions by Dynamic Programming. GCPR. Proceedings. Springer. LNCS 10496 255-267\par \par  Uhlmann, V, Haubold, C, Hamprecht, F A and Unser, M (2017). Diverse Shortest Paths for Bioimage Analysis. Bioinformatics. 1-3\par \par  Wolf, S, Schott, L, K\'f6the, U and Hamprecht, F A (2017). Learned Watershed: End-to-End Learning of Seeded Segmentation. ICCV. 2030-2038\par \par  Kandemir, M, Hamprecht, F A, Wojek, C and Schmidt, U (2017). Maschinelles Lernen. Patent, Patent Number WO2017032775A1\par \par  Beier, T, Pape, C, Rahaman, N, Prange, T, Berg, S, Bock, D, Cardona, A, Knott, G W, Plaza, S M, Scheffer, L K, K\'f6the, U, Kreshuk, A and Hamprecht, F A (2017). Multicut brings automated neurite segmentation closer to human performance. Nature Methods. 14 101-102. http://rdcu.be/oVDQ\par \par  Krasowki, N, Beier, T, Knott, G W, K\'f6the, U, Hamprecht, F A and Kreshuk, A (2017). Neuron Segmentation with High-Level Biological Priors. IEEE Transactions on Medical Imaging. 37\par \par  Ulman, V, Ma?ka, M, Magnusson, K E G, Ronneberger, O, Haubold, C, Harder, N, Matula, P, Matula, P, Svoboda, D, Radojevic, M, Smal, I, Rohr, K, Jald\'e9n, J, Blau, H M, Dzyubachyk, O, Lelieveldt, B, Xiao, P, Li, Y, Cho, S - Y, Dufour, A, Olivo-Marin, J C, Reyes-Aldasoro, C C, Solis-Lemus, J A, Bensch, R, Brox, T, Stegmaier, J, Mikut, R, Wolf, S, Hamprecht, F A, Esteves, T, Quelhas, P, Demirel, \'d6, Malstr\'f6m, L, Jug, F, Toman?\'e1k, P, Meijering, E, Mu\'f1oz-Barrutia, A, Kozubek, M and Ortiz-de-Solorzano, C (2017). An Objective Comparison of Cell Tracking Algorithms. Nature Methods. 14 1141-1152\par \par  Peter, S, Kirschbaum, E, Both, M, Campbell, L A, Harvey, B K, Heins, C, Durstewitz, D, Diego, F and Hamprecht, F A (2017). Sparse convolutional coding for neuronal assembly detection. NIPS, poster\par \par  Hau\'dfmann, M, Hamprecht, F A and Kandemir, M (2017). Variational Bayesian Multiple Instance Learning with Gaussian Processes. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 6570-6579\par \par  Beier, T, Andres, B, K\'f6the, U and Hamprecht, F A (2016). An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem. ECCV. Proceedings. Springer. LNCS 9906 715-730\par \par  von Borstel, M, Kandemir, M, Schmidt, P, Rao, M, Rajamani, K and Hamprecht, F A (2016). Gaussian process density counting from weak supervision. ECCV. Proceedings. Springer. LNCS 9905 365-380 \par \par  Haubold, C, Ales, J, Wolf, S and Hamprecht, F A (2016). A Generalized Successive Shortest Paths Solver for Tracking Dividing Targets. ECCV. Proceedings. Springer. LNCS 9911 566-582\par \par  Meijering, E, Carpenter, A E, Peng, H, Hamprecht, F A and Olivo-Marin, J (2016). Imagining the future of bioimage analysis. Nature Biotechnology. 34 1250-1255\par \par  Schiegg, M, Diego, F and Hamprecht, F A (2016). Learning Diverse Models: The Coulomb Structured Support Vector Machine. ECCV. Proceedings. Springer. LNCS 9907 585-599\par \par  Haubold, C, Schiegg, M, Kreshuk, A, Berg, S, K\'f6the, U and Hamprecht, F A (2016). Segmenting and Tracking Multiple Dividing Targets Using ilastik. Focus on Bio-Image Informatics. Springer. 219 199-229\par \par  Diego, F and Hamprecht, F A (2016). Structured Regression Gradient Boosting. CVPR. Proceedings. 1459-1467\par \par  Kandemir, M, Hau\'dfmann, M, Diego, F, Rajamani, K, van der Laak, J and Hamprecht, F A (2016). Variational weakly-supervised Gaussian processes. BMVC. Proceedings\par \par  Kleesiek, J, Petersen, J, D\'f6ring, M, Maier-Hein, K, K\'f6the, U, Wick, W, Hamprecht, F A, Bendszus, M and Biller, A (2016). Virtual Raters for Reproducible and Objective Assessments in Radiology. Nature Scientific Reports. 6\par \par  Kreshuk, A, Walecki, R, K\'f6the, U, Gierthm\'fchlen, M, Plachta, D, Genoud, C, Haastert-Talini, K and Hamprecht, F A (2015). Automated Tracing of Myelinated Axons and Detection of the Nodes of Ranvier in Serial Images of Peripheral Nerves. Journal of Microscopy. 259 (2) 143-154\par \par  Kandemir, M and Hamprecht, F A (2015). Cell event detection in phase-contrast microscopy sequences from few annotations. MICCAI. Proceedings. Springer. LNCS 9351 316-323\par \par  Kappes, J H, Andres, B, Hamprecht, F A, Schn\'f6rr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Kr\'f6ger, T, Lellmann, J, Komodakis, N, Savchynskyy, B and Rother, C (2015). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. Int.~J.~Comp.~Vision\par \par  Kappes, J H, Andres, B, Hamprecht, F A, Schn\'f6rr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Kr\'f6ger, T, Lellmann, J, Komodakis, N, Savchynskyy, B and Rother, C (2015). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. International Journal of Computer Vision. 1-30\par \par  Kappes, J H, Andres, B, Hamprecht, F A, Schn\'f6rr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Kr\'f6ger, T, Lellmann, J, Komodakis, N, Savchynskyy, B and Rother, C (2015). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. International Journal of Computer Vision. 115 155?184\par \par  Kappes, J H, Andres, B, Hamprecht, F A, Schn\'f6rr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Kr\'f6ger, T, Lellmann, J, Komodakis, N, Savchynskyy, B and Rother, C (2015). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. International Journal of Computer Vision. 115 155?184\par \par  Kappes, J H, Andres, B, Hamprecht, F A, Schn\'f6rr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Kr\'f6ger, T, Lellmann, J, Komodakis, N, Savchynskyy, B and Rother, C (2015). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. International Journal of Computer Vision. 115 155?184. http://hci.iwr.uni-heidelberg.de/opengm2/\par \par  Kandemir, M and Hamprecht, F A (2015). The Deep Feed-Forward Gaussian Process: An Effective Generalization to Covariance Priors. NIPS. Proceedings. 44 145-159\par \par  Beier, T, Hamprecht, F A and Kappes, J H (2015). Fusion Moves for Correlation Clustering. CVPR. Proceedings. 3507-3516\par \par  Schiegg, M, Hanslovsky, P, Haubold, C, K\'f6the, U, Hufnagel, L and Hamprecht, F A (2015). Graphical Model for Joint Segmentation and Tracking of Multiple Dividing Cell. Bioinformatics. 31 948-956. http://bioinformatics.oxfordjournals.org/content/early/2014/11/17/bioinformatics.btu764.full.pdf?keytype=ref&ijkey=mTXWsiFrci7R8tc\par \par  Krasowski, N, Beier, T, Knott, G W, K\'f6the, U, Hamprecht, F A and Kreshuk, A (2015). Improving 3D EM Data Segmentation by Joint Optimization over Boundary Evidence and Biological Priors. 12th \{IEEE\} International Symposium on Biomedical Imaging, \{ISBI\} 2015, Brooklyn, NY, USA, April 16-19, 2015. 536-539\par \par  Funke, J, Hamprecht, F A and Zhang, C (2015). Learning to Segment: Training Hierarchical Segmentation under a Topological Loss. MICCAI. Proceedings, Part III. Springer. 9351 268-275\par \par  Schiegg, M, Heuer, B, Haubold, C, Wolf, S, K\'f6the, U and Hamprecht, F A (2015). Proof-reading Guidance in Cell Tracking by Sampling from Tracking-by-assignment Models. ISBI. Proceedings. 394-398\par \par  Cali, C, Baghabra, J, Boges, D J, Holst, G R, Kreshuk, A, Hamprecht, F A, Srinivasan, M, Lehv\'e4slaiho, H and Magistretti, P J (2015). Three-dimensional immersive virtual reality for studying cellular compartments in 3D models from EM preparations of neural tissues. Journal of Comparative Neurology. 524 23-38\par \par  Kreshuk, A, Funke, J, Cardona, A and Hamprecht, F A (2015). Who is talking to whom: synaptic partner detection in anisotropic volumes of insect brain. MICCAI. Proceedings. Springer. LNCS 9349 661-668\par \par  Lou, X, Schiegg, M and Hamprecht, F A (2014). Active Structured Learning for Cell Tracking: Algorithm, Framework and Usability. IEEE Transactions on Medical Imaging. 33 (4) 849-860\par \par  Kr\'f6ger, T, Kappes, J H, Beier, T, K\'f6the, U and Hamprecht, F A (2014). Asymmetric Cuts: Joint Image Labeling and Partitioning. Pattern Recognition - 36th German Conference, \{GCPR\} 2014, M\'fcnster, Germany, September 2-5, 2014, Proceedings. http://dx.doi.org/10.1007/978-3-319-11752-2_16\par \par  Kr\'f6ger, T, Kappes, J H, Beier, T, K\'f6the, U and Hamprecht, F A (2014). Asymmetric Cuts: Joint Image Labeling and Partitioning. 36th German Conference on Pattern Recognition\par \par  Tek, B F, Kr\'f6ger, T, Mikula, S and Hamprecht, F A (2014). Automated Cell Nucleus Detection for Large-Volume Electron Microscopy of Neural Tissue. ISBI. Proceedings. 69-72\par \par  Kreshuk, A, K\'f6the, U, Pax, E, Bock, D D and Hamprecht, F A (2014). Automated Detection of Synapses in Serial Section Transmission Electron Microscopy Image Stacks. PLoS ONE. 9 2\par \par  Zhang, C, Yarkony, J and Hamprecht, F A (2014). Cell detection and segmentation using correlation clustering. MICCAI. Proceedings. Springer. 9-16\par \par  Kappes, J H, Andres, B, Hamprecht, F A, Schn\'f6rr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Kr\'f6ger, T, Lellmann, J, Komodakis, N, Savchynskyy, B and Rother, C (2014). A Comparative Study of Modern Inference Techniques for StructuredDiscrete Energy Minimization Problems. CoRR. http://arxiv.org/abs/1404.0533\par \par  Kappes, J H, Andres, B, Hamprecht, F A, Schn\'f6rr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Kr\'f6ger, T, Lellmann, J, Komodakis, N, Savchynskyy, B and Rother, C (2014). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. CoRR. abs/1404.0533. http://hci.iwr.uni-heidelberg.de/opengm2/\par \par  Kandemir, M and Hamprecht, F A (2014). Computer-aided diagnosis from weak supervision: A benchmarking study. Computerized Medical Imaging and Graphics. 42 44-50\par \par  Beier, T, Kr\'f6ger, T, Kappes, J H, K\'f6the, U and Hamprecht, F A (2014). Cut, Glue and Cut: A Fast, Approximate Solver for Multicut Partitioning. 2014 \{IEEE\} Conference on Computer Vision and Pattern Recognition, \{CVPR\} 2014, Columbus, OH, USA, June 23-28, 2014. http://dx.doi.org/10.1109/CVPR.2014.17\par \par  Decker, C and Hamprecht, F A (2014). Detecting individual body parts improves mouse behavior classification. Workshop on visual observation and analysis of Vertebrate And Insect Behavior (VAIB), 22nd International Conference on Pattern Recognition (ICPR). Proceedings\par \par  Kandemir, M, Feuchtinger, A, Walch, A and Hamprecht, F A (2014). Digital Pathology: Multiple instance learning can detect Barrett'scancer. ISBI. Proceedings. 1348-1351\par \par  Kandemir, M, Zhang, C and Hamprecht, F A (2014). Empowering multiple instance histopathology cancer diagnosis by cell graphs. MICCAI. Proceedings. Springer. 8674 228-235\par \par  Kandemir, M, Rubio, J C, Schmidt, U, Welbl, J, Ommer, B and Hamprecht, F A (2014). Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures. MICCAI. Proceedings. Springer. 154-161\par \par  Kandemir, M, Rubio, J C, Schmidt, U, Wojek, C, Welbl, J, Ommer, B and Hamprecht, F A (2014). Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures. Medical Image Computing and Computer-Assisted Intervention. Springer. 154--161\par \par  Lindner, R, Lou, X, Reinstein, J, Shoeman, R L, Hamprecht, F A and Winkler, A (2014). Hexicon 2: Automated Processing of Hydrogen-Deuterium Exchange Mass Spectrometry Data with Improved Deuteration Distribution Estimation. Journal of The American Society for Mass Spectrometry. 25 1018-1028\par \par  Kleesiek, J, Biller, A, Urban, G, K\'f6the, U, Bendszus, M and Hamprecht, F A (2014). ilastik for Multi-modal Brain Tumor Segmentation. MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, 3rdplace. 12-17\par \par  Kandemir, M and Hamprecht, F A (2014). Instance Label Prediction by Dirichlet Process Multiple Instance Learning. UAI. Proceedings\par \par  Urban, G, Bendszus, M, Hamprecht, F A and Kleesiek, J (2014). Multi-modal Brain Tumor Segmentation using Deep Convolutional NeuralNetworks. MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, winningcontribution. 31-35\par \par  Straehle, C N, Kandemir, M, K\'f6the, U and Hamprecht, F A (2014). Multiple instance learning with response-optimized random forests. ICPR. Proceedings. 3768 - 3773\par \par  Yarkony, J, Beier, T, Baldi, P and Hamprecht, F A (2014). Parallel Multicut Segmentation via Dual Decomposition. 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. http://dx.doi.org/10.1007/978-3-319-17876-9_4\par \par  Maco, B, Cantoni, M, Holtmaat, A, Kreshuk, A, Hamprecht, F A and Knott, G W (2014). Semiautomated Correlative 3D Electron Microscopy of In Vivo Imaged Axons and Dendrites. Nature Protocols. 9 1354-1366\par \par  Drory, A, Haubold, C, Avidan, S and Hamprecht, F A (2014). Semi-Global Matching: A Principled Derivation in Terms of Message Passing. GCPR. Proceedings. 43-53\par \par  K\'f6the, U, Herrmannsd\'f6rfer, F, Kats, I and Hamprecht, F A (2014). SimpleSTORM: a fast, self-calibrating reconstruction algorithm for localization microscopy. Histochemistry and Cell Biology. 141 613-627\par \par  Diego, F and Hamprecht, F A (2014). Sparse Space-Time Deconvolution for Calcium Image Analysis. NIPS. Proceedings. 64-72. http://papers.nips.cc/paper/5342-sparse-space-time-deconvolution-for-calcium-image-analysis\par \par  Lou, X, Kloft, M, R\'e4tsch, G and Hamprecht, F A (2014). Structured Learning from Cheap Data. Advanced Structured Prediction. The MIT Press\par \par  Fiaschi, L, Diego, F, Grosser, K - H, Schiegg, M, K\'f6the, U, Zlatic, M and Hamprecht, F A (2014). Tracking indistinguishable translucent objects over time using weakly supervised structured learning. CVPR. Proceedings. 2736 - 2743\par \par  Zhang, C, Huber, F, Knop, M and Hamprecht, F A (2014). Yeast Cell Detection and Segmentation in Bright Field Microscopy. ISBI. Proceedings. IEEE Computer Society. 1267-1270\par \par  Diego, F, Reichinnek, S, Both, M and Hamprecht, F A (2013). Automated Identification of Neuronal Activity from Calcium Imaging by Sparse Dictionary Learning. ISBI 2013. Proceedings. 1058-1061\par \par  Mikut, R, Dickmeis, T, Driever, W, Geurts, P, Hamprecht, F A, Kausler, B X, Ledesma-Carbayo, M, Mare?e, R, Mikula, K, Pantazis, P, Ronneberger, O, Santos, A and Stotzka, R (2013). Automated Processing of Zebrafish Imaging Data: A Survey. Zebrafish. 10 (3)\par \par  Kappes, J H, Andres, B, Hamprecht, F A, Schn\'f6rr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Lellmann, J, Komodakis, N and Rother, C (2013). A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problem. CVPR\par \par  Kappes, J H, Andres, B, Hamprecht, F A, Schn\'f6rr, C, Nowozin, S, Batra, D, Sungwoong, K, Kausler, B X, Lellmann, J, Komodakis, N and Rother, C (2013). A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems. CVPR 2013. Proceedings\par \par  Schiegg, M, Hanslovsky, P, Kausler, B X, Hufnagel, L and Hamprecht, F A (2013). Conservation Tracking. ICCV 2013. Proceedings. 2928--2935\par \par  Maco, B, Holtmaat, A, Cantoni, M, Kreshuk, A, Straehle, C N, Hamprecht, F A and Knott, G W (2013). Correlative in vivo 2 photon and focused ion beam scanning electron microscopy of cortical neurons. PloS one. 8 (2)\par \par  Fiaschi, L, Grosser, K - H, Afonso, B, Zlatic, M and Hamprecht, F A (2013). Keeping Count: Leveraging Temporal Context to Count Heavily Overlapping Objects. ISBI 2013.Proceedings. 656-659\par \par  Straehle, C N, Peter, S, K\'f6the, U and Hamprecht, F A (2013). K-smallest Spanning Tree Segmentations. German Conference on Pattern Recognition (DAGM/GCPR). Proceedings. Springer. 375-384\par \par  Diego, F and Hamprecht, F A (2013). Learning Multi-Level Sparse Representation. NIPS. Proceedings. http://papers.nips.cc/paper/5076-learning-multi-level-sparse-representations\par \par  Diego, F and Hamprecht, F A (2013). Learning Multi-Level Sparse Representation for Identifying Neuronal Activity. Signal Processing with Adaptive Sparse Structured Representations Workshop (SPARS). Book of Abstracts\par \par  Kr\'f6ger, T, Mikula, S, Denk, W, K\'f6the, U and Hamprecht, F A (2013). Learning to Segment Neurons with Non-local Quality Measures. MICCAI 2013. Proceedings, part II. Springer. 8150 419-427\par \par  Straehle, C N, K\'f6the, U and Hamprecht, F A (2013). Weakly supervised learning of image partitioning using decision trees with structured split criteria. ICCV 2013. Proceedings. 1849-1856\par \par  Andres, B, K\'f6the, U, Kr\'f6ger, T, Helmstaedter, M, Briggmann, K L, Denk, W and Hamprecht, F A (2012). 3D Segmentation of SBFSEM Images of Neuropil by a Graphical Model over Supervoxel Boundaries. Medical Image Analysis. 16 (2012) 796-805\par \par  Hanselmann, M, R\'f6der, J, K\'f6the, U, Renard, B Y, Heeren, R M A and Hamprecht, F A (2012). Active Learning for Convenient Annotation and Classification of Secondary Ion Mass Spectrometry Images. Analytical Chemistry. 85 (1) 147-155\par \par  R\'f6der, J, Kunzmann, K, Nadler, B and Hamprecht, F A (2012). Active Learning with Distributional Estimates. UAI 2012. Proceedings. 715-725\par \par  Zechmann, C M, Menze, B H, Kelm, B Michael, Zamecnik, P, Ikinger, U, Waldherr, R, Delorme, S, Hamprecht, F A and Bachert, P (2012). Automated vs. manual pattern recognition of 3D 1H MRSI data of patients with prostate cancer. Academic Radiology. 19, 6 675-684\par \par  Kausler, B X, Schiegg, M, Andres, B, Lindner, M, K\'f6the, U, Leitte, H, Wittbrodt, J, Hufnagel, L and Hamprecht, F A (2012). A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness. ECCV 2012. Proceedings. 7574 144-157\par \par  Funke, J, Andres, B, Hamprecht, F A, Cardona, A and Cook, M (2012). Efficient Automatic 3D-Reconstruction of Branching Neurons from EM Data. CVPR 2012. Proceedings. 1004-1011\par \par  Andres, B, Kr\'f6ger, T, Briggmann, K L, Denk, W, Norogod, N, Knott, G W, K\'f6the, U and Hamprecht, F A (2012). Globally Optimal Closed-Surface Segmentation for Connectomics. ECCV 2012. Proceedings, Part 3. 778-791\par \par  Andres, B, Kappes, J H, Beier, T, K\'f6the, U and Hamprecht, F A (2012). The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models. ECCV 2012\par \par  Andres, B, Kappes, J H, Beier, T, K\'f6the, U and Hamprecht, F A (2012). The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models. Computer Vision - \{ECCV\} 2012 - 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part \{VII\}. http://dx.doi.org/10.1007/978-3-642-33786-4_12\par \par  Andres, B, Kappes, J Hendrik, Beier, T, K\'f6the, U and Hamprecht, F A (2012). The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models. ECCV 2012\par \par  Fiaschi, L, Nair, R, K\'f6the, U and Hamprecht, F A (2012). Learning to Count with Regression Forest and Structured Labels. ICPR 2012. Proceedings. 2685-2688\par \par  Lou, X and Hamprecht, F A (2012). Learning to Segment Dense Cell Nuclei with Shape Prior. CVPR 2012. Proceedings. 1012-1018\par \par  Sommer, C, Fiaschi, L, Hamprecht, F A and Gerlich, D (2012). Learning-based Mitotic Cell Detection in Histopathological Images. ICPR 2012. Proceedings. 2306-2309\par \par  Horva?t, E - A, Hanselmann, M, Hamprecht, F A and Zweig, K A (2012). One plus one makes three (for social networks). PLoS ONE. 4,7\par \par  Renard, B Y, Xu, B, Kirchner, M, Zickmann, F, Winter, D, Korten, S, Brattig, N, Tzur, A, Hamprecht, F A and Steen, H (2012). Overcoming species boundaries in peptide identification with BICEPS. Molecular and Cellular Proteomics. 11\par \par  Lou, X, Fiaschi, L, K\'f6the, U and Hamprecht, F A (2012). Quality Classification of Microscopic Imagery with Weakly Supervised Learning. MICCAI-MLMI. Proceedings. 176-183\par \par  Straehle, C N, K\'f6the, U, Briggman, K, Denk, W and Hamprecht, F A (2012). Seeded watershed cut uncertainty estimators for guided interactive segmentation. CVPR 2012. Proceedings. 765 - 772\par \par  Lou, X and Hamprecht, F A (2012). Structured Learning from Partial Annotations. ICML 2012. Proceedings. http://icml.cc/discuss/2012/753.html\par \par  Horva?t, E - A, Hanselmann, M, Hamprecht, F A and Zweig, K A (2012). You Are Who Knows You: Predicting Links Between Non-Members of Facebook. European Conference on Complex Systems. Proceedings. 3 309-315\par \par  Kreshuk, A, Straehle, C N, Sommer, C, K\'f6the, U, Cantoni, M, Knott, G W and Hamprecht, F A (2011). Automated Detection and Segmentation of Synaptic Contacts in Nearly Isotropic Serial Electron Microscopy Images. PLoS ONE. 6 (10)\par \par  Kreshuk, A, Straehle, C N, Sommer, C, K\'f6the, U, Knott, G W and Hamprecht, F A (2011). Automated Segmentation of Synapses in 3D EM Data. Eighth IEEE International Symposium on Biomedical Imaging (ISBI 2011).Proceedings. 220-223\par \par  Straehle, C N, K\'f6the, U, Knott, G W and Hamprecht, F A (2011). Carving: Scalable Interactive Segmentation of Neural Volume Electron Microscopy Images. MICCAI 2011, Proceedings. Springer. 6891 653-660\par \par  Kaster, F O, Weber, M - A and Hamprecht, F A (2011). Comparative Validation of Graphical Models for Learning Tumor Segmentations from Noisy Manual Annotations. LNCS. Springer, Heidelberg. LNCS 6533 74-85\par \par  Lou, X, Kaster, F O, Lindner, M, Kausler, B X, K\'f6the, U, H\'f6ckendorf, B, Wittbrodt, J, J\'e4nicke, H and Hamprecht, F A (2011). DELTR: Digital Embryo Lineage Tree Reconstructor. Eighth IEEE International Symposium on Biomedical Imaging (ISBI). Proceedings. 1557-1560\par \par  Wanner, S, Sommer, C, Rocholz, R, Jung, M, Hamprecht, F A and J\'e4hne, B (2011). A framework for interactive visualization and classification of dynamical processes at the water surface. 16th International Workshop on Vision, Modelling and Visualization. Eurographics Association, Germany. 199--206\par \par  Wanner, S, Sommer, C, Rocholz, R, Hamprecht, F A and J\'e4hne, B (2011). A Framework for Interactive Visualization and Classification of Dynamical Processes at the Water Surface. 16th International Workshop on Vision, Modelling and Visualization. Eurographics Association, Germany. 199-206\par \par  R\'f6der, J, Tolosana-Delgado, R and Hamprecht, F A (2011). Gaussian process classification: singly versus doubly stochastic models, and new computational schemes. Stochastic Environmental Research & Risk Assessment. 25 (7) 865-879\par \par  Sommer, C, Straehle, C N, K\'f6the, U and Hamprecht, F A (2011). ilastik: Interactive Learning and Segmentation Toolkit. Eighth IEEE International Symposium on Biomedical Imaging (ISBI 2011).Proceedings. 230-233\par \par  Frank, M and Hamprecht, F A (2011). Image-Based Supervision of a Periodically Working Machine. Pattern Analysis and Applications. 1-10\par \par  Kaster, F O, Merkel, B, Nix, O and Hamprecht, F A (2011). An object-oriented library for systematic training and comparison of classifiers for computer-assisted tumor diagnosis from MRSI measurements. Computer Science - Research and Development. 26 65-85\par \par  Menze, B H, Kelm, B Michael, Splitthoff, N, K\'f6the, U and Hamprecht, F A (2011). On oblique random forests. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2011. Proceedings. Springer. 453-469\par \par  Andres, B, Kappes, J H, Beier, T, K\'f6the, U and Hamprecht, F A (2011). Probabilistic Image Segmentation with Closedness Constraints. Proceedings of ICCV\par \par  Andres, B, Kappes, J H, Beier, T, K\'f6the, U and Hamprecht, F A (2011). Probabilistic Image Segmentation with Closedness Constraints. ICCV, Proceedings. 2611 - 2618\par \par  Andres, B, Kappes, J H, Beier, T, K\'f6the, U and Hamprecht, F A (2011). Probabilistic Image Segmentation with Closedness Constraints. Proceedings of ICCV\par \par  Hanselmann, M, Voss, B, Renard, B Y, Lindner, M, K\'f6the, U, Kirchner, M and Hamprecht, F A (2011). SIMA: Simultaneous Multiple Alignment of LC/MS Peak Lists. Bioinformatics. 27 (7) 987-993\par \par  Lou, X and Hamprecht, F A (2011). Structured Learning for Cell Tracking. NIPS 2011. Proceedings. 1296-1304\par \par  Kelm, B Michael, Kaster, F O, Henning, A, Weber, M - A, Bachert, P, B\'f6singer, P, Hamprecht, F A and Menze, B H (2011). Using Spatial Prior Knowledge in the Spectral Fitting of Magnetic Resonance Spectroscopic Images. NMR in Biomedicine. 25(1) 1-13\par \par  Pfannm\'f6ller, M, Fl\'fcgge, H, Benner, G, Wacker, I, Sommer, C, Hanselmann, M, Schmale, S, Schmidt, H, Hamprecht, F A, Rabe, T, Kowalsky, W and Schr\'f6der, R (2011). Visualizing a homogeneous blend in bulk heterojunction polymer solar cells by analytical electron microscopy. Nano Letters. 11 3099-3107\par \par  Kreshuk, A, Stankiewicz, M, Lou, X, Kirchner, M, Hamprecht, F A and Mayer, M P (2010). Automated detection and analysis of bimodal isotope peak distribution in H/D exchange mass spectrometry using HeXicon. International Journal of Mass Spectrometry. 302 125-131\par \par  Kirchner, M, Renard, B Y, K\'f6the, U, Pappin, D J, Hamprecht, F A, Steen, J A J and Steen, H (2010). Computational Protein Profile Similarity Screening for Quantitative Mass Spectrometry Experiments. Bioinformatics. 26 (1) 77-83\par \par  Lou, X, Kirchner, M, Renard, B Y, K\'f6the, U, Graf, C, Lee, C, Steen, J A J, Steen, H, Mayer, M P and Hamprecht, F A (2010). Deuteration Distribution Estimation with Improved Sequence Coverage for HX/MS Experiments. Bioinformatics. 26(12) 1535-1541\par \par  Andres, B, Kappes, J H, K\'f6the, U, Schn\'f6rr, C and Hamprecht, F A (2010). An Empirical Comparison of Inference Algorithms for Graphical Modelswith Higher Order Factors Using OpenGM. Pattern Recognition, Proc.~32th DAGM Symposium. 353-362\par \par  Andres, B, Kappes, J H, K\'f6the, U, Schn\'f6rr, C and Hamprecht, F A (2010). An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM. Pattern Recognition, Proc.~32th DAGM Symposium\par \par  Renard, B Y, Timm, W, Kirchner, M, Steen, J A J, Hamprecht, F A and Steen, H (2010). Estimating the Confidence of Peptide Identifications without Decoy Databases. Analytical Chemistry. 4314-4318\par \par  K\'f6the, U, Andres, B, Kr\'f6ger, T and Hamprecht, F A (2010). Geometric Analysis of 3D Electron Microscopy Data. Proceedings of Workshop on Discrete Geometry and Mathematical Morphology (WADGMM). 22-26\par \par  Andres, B, K\'f6the, U, Kr\'f6ger, T and Hamprecht, F A (2010). How to Extract the Geometry and Topology from Very Large 3D Segmentations. ArXiv e-prints. http://arxiv.org/abs/1009.6215\par \par  Andres, B, Kappes, J H, K\'f6the, U and Hamprecht, F A (2010). The Lazy Flipper: MAP Inference in Higher-Order Graphical Models by Depth-limited Exhaustive Search. ArXiv e-prints. http://arxiv.org/abs/1009.4102\par \par  Kirchner, M, Steen, J A J, Hamprecht, F A and Steen, H (2010). MGFp: An Open Mascot Generic Format Parser Library Implementation. Journal of Proteome Research. 9 (5) 27622763\par \par  Menze, B H and Hamprecht, F A (2010). Multimodal Medical Image Analysis: from Visualization to Disease Modeling. Zeitschrift f\'fcr Med. Physik. 1 1-2\par \par  Kaster, F O, Kassemeyer, S, Merkel, B, Nix, O and Hamprecht, F A (2010). An object-oriented library for systematic training and comparison of classifiers for computer-assisted tumor diagnosis from MRSI measurements. Bildverarbeitung f\'fcr die Medizin 2010 -- Algorithmen, Systeme, Anwendungen. Springer. 97-101\par \par  Andres, B, K\'f6the, U, Kr\'f6ger, T and Hamprecht, F A (2010). Runtime-Flexible Multi-dimensional Views and Arrays for C++98 and C++0x. ArXiv e-prints. http://arxiv.org/abs/1008.2909v1\par \par  G\'f6rlitz, L, Hamprecht, F A and Staudacher, M (2009). Allocation of particles to development processes. Patent\par \par  Hayn, M, Beirle, S, Hamprecht, F A, Platt, U, Menze, B H and Wagner, T (2009). Analysing spatio-temporal patterns of the global NO{\sub 2}-distribution retrieved frome GOME satellite observations using a generalized additive model. Atmospheric Chemistry and Physics. 9 9367-9398\par \par  J\'e4ger, M, Kiel, A, Herten, D - P and Hamprecht, F A (2009). Analysis of Single-Molecule Fluorescence Spectroscopic Data with a Markov Modulated Poisson Process. ChemPhysChem. 10:14 2486-2495\par \par  Kaster, F O, Kelm, B Michael, Zechmann, C M, Weber, M - A, Hamprecht, F A and Nix, O (2009). Classification of Spectroscopic Images in the DIROlab Environment. World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany. Springer. 25/V 252--255\par \par  Menze, B H, Kelm, B Michael, Masuch, R, Himmelreich, U, Bachert, P, Petrich, W and Hamprecht, F A (2009). A Comparison of Random Forest and its Gini Importance with Standard Chemometric Methods for the Feature Selection and Classification of Spectral Data. BMC Bioinformatics. 10:213\par \par  Frank, M, Plaue, M and Hamprecht, F A (2009). Denoising of Continuous-Wave Time-Of-Flight Depth Images Using Confidence Measures. Optical Engineering. 48, 077003\par \par  Kelm, B Michael, Menze, B H, Nix, O, Zechmann, C M and Hamprecht, F A (2009). Estimating Kinetic Parameter Maps from Dynamic Contrast-Enhanced MRI using Spatial Prior Knowledge. IEEE Transaction on Medical Imaging. 28:10 1534-1547\par \par  Hanselmann, M, K\'f6the, U, Renard, B Y, Kirchner, M, Heeren, R M A and Hamprecht, F A (2009). Multivariate Watershed Segmentation of Compositional Data. Proceedings of the 15th International Conference on Discrete Geometry for Computer Imagery (DGCI), in press. Springer. 5810 180-192\par \par  Trittler, S and Hamprecht, F A (2009). Near-Optimum Sampling Design and an Efficient Algorithm for Single Tone Frequency Estimation. Digital Signal Processing. 19 628-639\par \par  G\'f6rlitz, L, Menze, B H, Kelm, B Michael and Hamprecht, F A (2009). Processing Spectral Data. Surface and Interface Analysis. 41 636-644\par \par  Andres, B, K\'f6the, U, Bonea, A, Nadler, B and Hamprecht, F A (2009). Quantitative Assessment of Image Segmentation Quality by Random Walk Relaxation Times. Pattern Recognition. 31st DAGM Symposium, Jena, Germany, September 9-11, 2009. Proceedings. Springer. 5748 502-511\par \par  Staudacher, M, Hamprecht, F A and G\'f6rlitz, L (2009). Self Adjustment of Scanning Electron Microscopes / Selbstadaptivit\'e4t von Rasterelektronenmikroskopen. Patent, Patent Number  WO2009062781A1\par \par  Frank, M, Plaue, M, Rapp, H, K\'f6the, U, J\'e4hne, B and Hamprecht, F A (2009). Theoretical and experimental error analysis of continuous-wave time-of-flight range cameras. Opt. Eng. 48 013602\par \par  Frank, M, Plaue, M, Rapp, H, K\'f6the, U, J\'e4hne, B and Hamprecht, F A (2009). Theoretical and Experimental Error Analysis of Continuous-Wave Time-Of-Flight Range Cameras. Optical Engineering. 48, 013602\par \par  Hanselmann, M, K\'f6the, U, Kirchner, M, Renard, B Y, Amstalden, E R, Glunde, K, Heeren, R M A and Hamprecht, F A (2009). Towards Digital Staining using Imaging Mass Spectrometry and Random Forests. Journal of Proteome Research. 8 3558-3567\par \par  Renard, B Y, Kirchner, M, Monigatti, F, Ivanov, A R, Rappsilber, J, Winter, D, Steen, J A J, Hamprecht, F A and Steen, H (2009). When Less Can Yield More - Computational Preprocessing of MS/MS Spectra for Peptide Identification Preprocessing. Proteomics. 9 4978-4984\par \par  Hanselmann, M, Kirchner, M, Renard, B Y, Amstalden, E R, Glunde, K, Heeren, R M A and Hamprecht, F A (2008). Concise Representation of MS Images by Probabilistic Latent Semantic Analysis. Analytical Chemistry. 80 9649-9658\par \par  Steen, J A J, Steen, H, Georgi, A, Parker, K C, Springer, M, Kirchner, M, Hamprecht, F A and Kirschner, M W (2008). Different Phosphorylation States of the Anaphase Promoting Complex in Response to Anti-Mitotic Drugs: A Quantitative Proteomic Analysis. Proceedings of the National Academy of Sciences. 105 6069-6074\par \par  Andres, B, Kondermann, C, Kondermann, D, Hamprecht, F A and Garbe, C S (2008). On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008. IEEE. 1--6\par \par  Andres, B, Kondermann, C, Kondermann, D, K\'f6the, U, Hamprecht, F A and Garbe, C S (2008). On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation. Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on. 1-6\par \par  Staudacher, M, Hamprecht, F A and G\'f6rlitz, L (2008). Method for processing an intensity image of a microscope. Patent, Patent Number: WO2008034721A1\par \par  Menze, B H, Kelm, B Michael, Weber, M - A, Bachert, P and Hamprecht, F A (2008). Mimicking the human expert: pattern recognition for an automated assessment of data quality in MRSI. Magnetic Resonance in Medicine. 59 1457-1466\par \par  Renard, B Y, Kirchner, M, Steen, H, Steen, J A J and Hamprecht, F A (2008). NITPICK: Peak Identification for Mass Spectrometry Data. BMC Bioinformatics. 9 355\par \par  J\'e4ger, M and Hamprecht, F A (2008). Principal Component Imagery for the Quality Monitoring of Dynamic Laser Welding Processes. IEEE Transactions on Industrial Electronics. 56:4 1307-1313\par \par  K\'f6nig, T, Menze, B H, Kirchner, M, Monigatti, F, Parker, K C, Patterson, T, Steen, J J, Hamprecht, F A and Steen, H (2008). Robust Prediction of the MASCOT Score for an Improved Quality Assessment in Mass Spectrometric Proteomics. Journal of Proteome Research. 7 3708-3717\par \par  Andres, B, K\'f6the, U, Helmstaedter, M, Denk, W and Hamprecht, F A (2008). Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification. Pattern Recognition. 30th DAGM Symposium Munich, Germany, June 10-13, 2008. Proceedings. Springer. 5096 142-152\par \par  J\'e4ger, M, Humbert, S and Hamprecht, F A (2008). Sputter Tracking for the Automatic Monitoring of Industrial Laser Welding Processes. IEEE Transactions on Industrial Electronics. 55 2177-2184\par \par  Rapp, H, Frank, M, Hamprecht, F A and J\'e4hne, B (2008). A theoretical and experimental investigation of the systematic errors and statistical uncertainties of time-of-flight cameras. Int. J. Intelligent Systems Technologies and Applications. 5 402--413\par \par  Rapp, H, Frank, M, Hamprecht, F A and J\'e4hne, B (2008). A Theoretical and Experimental Investigation of the Systematic Errors and Statistical Uncertainties of Time-of-Flight Cameras. Int. J. Intelligent Systems Technologies and Applications. 5 402-413\par \par  J\'e4ger, M, Knoll, C and Hamprecht, F A (2008). Weakly Supervised Learning of a Classifier for Unusual Event Detection. IEEE Transactions on Image Processing. 17 1700-1708\par \par  Kondermann, C, Kondermann, D, J\'e4hne, B, Garbe, C S, Schn\'f6rr, C and J\'e4hne, B (2007). An adaptive confidence measure for optical flows based on linear subspace projections. Proceedings of the 29th DAGM Symposium on Pattern Recognition. Springer. 4713 132--141\par \par  Kirchner, M, Saussen, B, Steen, H, Steen, J A J and Hamprecht, F A (2007). amsrpm: Robust Point Matching in Retention Time Alignment of LC/MS Data with R. Journal of Statistical Software. 18 1-12. http://www.jstatsoft.org/v18/i04/paper\par \par  Kelm, B Michael, Menze, B H, Zechmann, C M, Baudendistel, K T and Hamprecht, F A (2007). Automated Estimation of Tumor Probability in Prostate MRSI: Pattern Recognition vs. Quantification. Magnetic Resonance in Medicine. 57 150-159\par \par  Weber, C, Zechmann, C M, Kelm, B Michael, Zamecnik, R, Hendricks, D, Waldherr, R, Hamprecht, F A, Delorme, S, Bachert, P and Ikinger, U (2007). Comparison of correctness of manuel and automatic evaluation of MR-spectrum with prostrate cancer. Der Urologe. 46 1252\par \par  Garbe, C S, Schn\'f6rr, C and J\'e4hne, B (2007). Fluid flow estimation through integration of physical flow configurations. Proceedings of the 29th DAGM Symposium on Pattern Recognition. Springer. 92--101\par \par  Menze, B H, Kelm, B Michael and Hamprecht, F A (2007). From eigenspots to fisherspots -- latent spaces in the nonlinear detection of spot patterns in a highly variable background. Advances in data analysis. Springer. 33 255-262\par \par  Schm\'e4hling, J and Hamprecht, F A (2007). Generalizing the Abbott-Firestone curve by two new surface descriptors. Wear. 262 1360-1371\par \par  Menze, B H, Petrich, W and Hamprecht, F A (2007). Multivariate feature selection and hierarchical classification for infrared spectroscopy: serum-based detection of bovine spongiform encephalopathy. Analytical and Bioanalytical Chemistry. 387 1801-1807\par \par  (2007). Pattern Recognition ? 29th DAGM Symposium. LCNS. Springer. 4713\par \par  Schn\'f6rr, C and J\'e4hne, B (2007). Pattern Recognition, 29th DAGM Symposium, Heidelberg, Germany, September 12-14. Springer. 4713\par \par  (2007). Pattern Recognition, 29Th Dagm Symposium, Heidelberg, Germany, September 12-14, 2007, Proceedings. Springer\par \par  Andres, B, Garbe, C S, Schn\'f6rr, C and J\'e4hne, B (2007). Selection of local optical flow models by means of residual analysis. Proceedings of the 29th DAGM Symposium on Pattern Recognition. Springer. 72--81\par \par  Andres, B, Hamprecht, F A and Garbe, C S (2007). Selection of Local Optical Flow Models by Means of Residual Analysis. Pattern Recognition. Springer. 4713 72-81\par \par  G\'f6rlitz, L, Menze, B H, Weber, M - A and Kelm, B Michael (2007). Semi-Supervised Tumor Detection in MRSI With Discriminative Random Fields. Pattern Recognition. Springer. 4713 224-233\par \par  Rapp, H, Frank, M, Hamprecht, F A and J\'e4hne, B (2007). A theoretical and experimental investigation of the systematic errors and statistical uncertainties of time-of-flight cameras. Proc.\\ Dyn3D Workshop, Heidelberg, Sept. 11, 2007. ZESS, Univ.\\ Siegen\par \par  Kelm, B Michael, M\'fcller, N, Menze, B H and Hamprecht, F A (2006). Bayesian Estimation of Smooth Parameter Maps for Dynamic Contrast-Enhanced MR Images with Block-ICM. Proc Computer Vision and Pattern Recognition Workshop (Mathematical Methods in Biomedical Image Analysis). IEEE Computer Society. 96-103\par \par  Zechmann, C M, Kelm, B Michael, Zamecnik, P, Ikinger, U, Waldherr, R, R\'f6ll, S, Delorme, S, Hamprecht, F A and Bachert, P (2006). Can man still beat the machine? Automated vs. manual pattern recognition of 3D MRSI data of prostate cancer patients. Proceedings of the 16th ISMRM\par \par  Kelm, B Michael, Menze, B H, Neff, T, Zechmann, C M and Hamprecht, F A (2006). CLARET: a tool for fully automated evaluation of MRSI with pattern recognition methods.. Bildverarbeitung f\'fcr die Medizin 2006 - Algorithmen, Systeme, Anwendungen. Springer. 51-55. http://www.efmi-wg-mip.net/service/bvm2006\par \par  Carlsohn, M F, Menze, B H, Kelm, B Michael, Hamprecht, F A, Kercek, A, Leitner, R and Polder, G (2006). Color image processing. CRC Press. 7(17) 393-419\par \par  Lichy, M P, Bachert, P, Hamprecht, F A, Weber, M - A, Debus, J, Schulz-Ertner, D, Kauczor, H - U and Schlemmer, H - P (2006). Einsatz der 1H-MR-spektroskopischen Bildgebung in der Strahlentherapie: Cholin als Marker f\'fcr die Bestimmung der relativen Wahrscheinlichkeit eines Tumorprogresses nach Bestrahlung glialer Hirntumoren. Zeitung f\'fcr R\'f6ntgenforschung. 178 627-633\par \par  Menze, B H, Kelm, B Michael, Heck, D, Lichy, M P and Hamprecht, F A (2006). Machine-based rejection of low quality spectra and estimation of brain tumor probabilities from magnetic resonance spectroscopic images. Bildverarbeitung f\'fcr die Medizin. 31-36\par \par  Menze, B H, Lichy, M P, Bachert, P, Kelm, B Michael, Schlemmer, H P and Hamprecht, F A (2006). Optimal Classification of Long Echo Time in vivo Magnetic Resonance Spectra in the Detection of Recurrent Brain Tumor. NMR in Biomedicine. 19 599-609\par \par  Sieg, S, Stutz, B, Schmidt, T, Hamprecht, F A and Maier, W F (2006). A QCAR-approach to materials modelling. Journal of Molecular Modeling. 12 611-619\par \par  Schm\'e4hling, J, Hamprecht, F A and Hoffmann, D M P (2006). A three-dimensional measure of surface roughness based on mathematical morphology. International Journal of Machine Tools and Manufacture. 46 (14) 1764-1769\par \par  K\'f6nig, T, Hamprecht, F A and K\'fccherer, H (2005). On The Application Of Multiscale Motion Estimation In Intravascular Elastography. University of Heidelberg\par \par  Kelm, B Michael, Menze, B H and Hamprecht, F A (2005). Automatische Lokalisation von Tumoren in 1H-NMR-spektroskopischen in vivo Aufnahmen. VDI-Berichte. 1883 457-466\par \par  J\'e4ger, M, Knoll, C and Hamprecht, F A (2005). Automatisierte Klassifikation von Laserschwei\\DFprozessen durch Nutzung von 3D Signalverarbeitungs-Algorithmen. Robert Bosch GmbH, Schwieberdingen and IWR, Uni Heidelberg\par \par  Hissmann, M and Hamprecht, F A (2005). Bayesian surface estimation for white light interferometry. Optical Engineering. 44 1-9\par \par  G\'f6rlitz, L, Hamprecht, F A and Staudacher, M (2005). Detektion von Partikeln in Intensit\'e4tsbildern mit Hilfe eines morphologischen Skalenraumes. Robert-Bosch GmbH, University of Heidelberg\par \par  K\'fcnsch, H R, Agrell, E and Hamprecht, F A (2005). Optimal lattices for sampling. IEEE Transactions on Information Theory. 51 634-647\par \par  Zhang, H, Hamprecht, F A and Amann, A (2005). Report about VOCs Dataset's Analysis based on Random Forests. Proceedings of the HPC-Asia05. IEEE Computer Society Press. 603-607\par \par  Hamprecht, F A (2004). Classification. Practical Handbook on Image Processing for Scientific and Technical Applications. CRC Press. 509-519\par \par  Menze, B H, Wormit, M, Bachert, P, Lichy, M P, Schlemmer, H - P and Hamprecht, F A (2004). Classification of in vivo magnetic resonance spectra. Classification in ubiquitous challenge: Proceedings of the GfKl 2004. Springer. 362-369\par \par  Restle, J, Hissmann, M and Hamprecht, F A (2004). Nonparametric Smoothing of Height maps using ``Confidence'' values. Optical Engineering. 43 866-871\par \par  Hader, S and Hamprecht, F A (2004). Two-Stage Classification with Automatic Feature Selection for an Industrial Application. Classification, the ubiquitous challenge: Proceedings of GfKl 2004. Springer. 137-144\par \par  Hamprecht, F A and J\'e4hne, B (2004). Vom Bild zur Information. Ruperto Carola -- Forschungsmagazin der Universit\'e4t Heidelberg. 03.2004 9-12\par \par  Hamprecht, F A and J\'e4hne, B (2004). Vom Bild zur Information\par \par  Hissmann, M and Hamprecht, F A (2003). Bayessche Sch\'e4tzung von H\'f6henkarten aus der Wei\\DF licht-Interferometrie. Oberfl\'e4chenmesstechnik 2003. 187--196\par \par  Hader, S and Hamprecht, F A (2003). Efficient Density Clustering. Between Data Science and Applied Data Analysis. Springer. 39-48\par \par  Hamprecht, F A and Agrell, E (2003). Exploring a space of materials: spatial sampling design and subset selection. Experimental Design for Combinatorial and High Throughput Materials Development. Wiley\par \par  Eisele, H and Hamprecht, F A (2003). A new approach for defect detection in X-ray CT images. Pattern Recognition. Springer. 2449 345-352\par \par  Hamprecht, F A, Thiel, W and van Gunsteren, W F (2002). Chemical library subset selection algorithms: a unified derivation using spatial statistics. Journal of Chemical Information and Computer Sciences. 42 414-428\par \par  J\'e4hne, B, Brocke, M, Eisele, H, Hader, S, Hamprecht, F A, Happold, W, Raisch, F and Restle, J (2002). F\'fcr Anspruchsvolle - Multidimensionale Bildverarbeitung in der Produktion. Qualit\'e4t und Zuverl\'e4ssigkeit. 47 1154-1159\par \par  Gee, P J, Hamprecht, F A, Schuler, L D, van Gunsteren, W F, Duchardt, E, Schwalbe, H, Albert, M and Seebach, D (2002). A molecular dynamics simulation study of the conformational preferences of oligo-(3- hydroxyalcanoic acids) in chloroform solution. Helv. Chim. Acta. 85 618-632\par \par  J\'e4hne, B, Brocke, M, Eisele, H, Hader, S, Hamprecht, F A, Happold, W, Raisch, F and Restle, J (2002). Multidimensionale Bildverarbeitung in der Produktion. QZ. 47 1154--1159. http://www.qz-online.de/qz-zeitschrift/archiv/artikel/multidimensionale-bildverarbeitung-in-der-produktion-fuer-anspruchsvolle-338129.html\par \par  Hamprecht, F A, Achleitner, U, Krismer, A C, Lindner, K H, Wenzel, V, Strohmenger, H - U, Thiel, W and van Gunsteren, W F (2001). Fibrillation power: An alternative method of ECG spectral analysis for prediction of countershock success in a porcine model of ventricular fibrillation. Resuscitation. 50 287-296\par \par  Hamprecht, F A, Jost, D, R\'fcttimann, M, Calamai, F and Kowalski, J J (2001). Preliminary results on the prediction of countershock success with fibrillation power. Resuscitation. 50 297-299\par \par  Hamprecht, F A, Peter, C, Daura, X, Thiel, W and van Gunsteren, W F (2001). A strategy for analysis of (molecular) equilibrium simulations: configuration space density estimation, clustering and visualization. Journal of Chemical Physics. 114 2079-2089\par \par  Hamprecht, F A, Cohen, A J, Tozer, D J and Handy, N C (1998). Development and assessment of new exchange-correlation functionals. Journal of Chemical Physics. 109 6264-6271\par \par  B\'fchl, M and Hamprecht, F A (1998). Theoretical Investigation of NMR Chemical Shifts and Reactivities of Oxovanadium (V) Compounds. Journal of Computational Chemistry. 19 113-122\par \par  Kubinyi, H, Hamprecht, F A and Mietzner, T (1998). Threedimensional Quantitative Similarity-Activity Relationships (3DQSiAR) from SEAL Similarity Matrices. Journal of Medicinal Chemistry. 41 2553-2564\par \par  Hamprecht, F A, Scott, W R P and van Gunsteren, W F (1997). Generation of pseudo-native protein structures for threading. Proteins. 28 522-529\par \par }