Publications

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2013
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. 656-659PDF icon Technical Report (711.68 KB)
Straehle, C, Peter, S, Köthe, U and Hamprecht, F A (2013). K-smallest Spanning Tree Segmentations. German Conference on Pattern Recognition (DAGM/GCPR). Proceedings. Springer. 375-384PDF icon Technical Report (1.18 MB)
Diego, F and Hamprecht, F A (2013). Learning Multi-Level Sparse Representation. NIPS. Proceedings. http://papers.nips.cc/paper/5076-learning-multi-level-sparse-representationsPDF icon Technical Report (2.79 MB)
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 AbstractsPDF icon Technical Report (1.05 MB)
Kröger, T, Mikula, S, Denk, W, Köthe, U and Hamprecht, F A (2013). Learning to Segment Neurons with Non-local Quality Measures. MICCAI 2013. Proceedings, part II. Springer. 8150 419-427PDF icon Technical Report (2.87 MB)
Straehle, C, Köthe, U and Hamprecht, F A (2013). Weakly supervised learning of image partitioning using decision trees with structured split criteria. ICCV 2013. Proceedings. 1849-1856PDF icon Technical Report (5.97 MB)
2014
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) 849-860PDF icon Technical Report (6.84 MB)
Kröger, T, Kappes, J H, Beier, T, Köthe, U and Hamprecht, F A (2014). Asymmetric Cuts: Joint Image Labeling and Partitioning. Pattern Recognition - 36th German Conference, {GCPR} 2014, Münster, Germany, September 2-5, 2014, Proceedings. http://dx.doi.org/10.1007/978-3-319-11752-2_16PDF icon Technical Report (3.46 MB)
Tek, B F, Kröger, T, Mikula, S and Hamprecht, F A (2014). Automated Cell Nucleus Detection for Large-Volume Electron Microscopy of Neural Tissue. ISBI. Proceedings. 69-72PDF icon Technical Report (533.92 KB)
Kreshuk, A, Köthe, 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 2PDF icon Technical Report (16.66 MB)
Zhang, C, Yarkony, J and Hamprecht, F A (2014). Cell detection and segmentation using correlation clustering. MICCAI. Proceedings. Springer. 9-16PDF icon Technical Report (8.06 MB)
Kappes, J H, Andres, B, Hamprecht, F A, Schnörr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Kröger, 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. http://arxiv.org/abs/1404.0533
Kappes, J H, Andres, B, Hamprecht, F A, Schnörr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Kröger, 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/PDF icon Technical Report (3.32 MB)
Kandemir, M and Hamprecht, F A (2014). Computer-aided diagnosis from weak supervision: A benchmarking study. Computerized Medical Imaging and Graphics. 42 44-50PDF icon Technical Report (4.28 MB)
Beier, T, Kröger, T, Kappes, J H, Köthe, 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.2014.17PDF icon Technical Report (10.06 MB)
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). ProceedingsPDF icon Technical Report (1.48 MB)
Kandemir, M, Feuchtinger, A, Walch, A and Hamprecht, F A (2014). Digital Pathology: Multiple instance learning can detect Barrett'scancer. ISBI. Proceedings. 1348-1351PDF icon Technical Report (2.86 MB)
Kandemir, M, Zhang, C and Hamprecht, F A (2014). Empowering multiple instance histopathology cancer diagnosis by cell graphs. MICCAI. Proceedings. Springer. 8674 228-235PDF icon Technical Report (1.76 MB)
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. 154-161PDF icon Paper (2 MB)
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 1018-1028PDF icon Technical Report (2.1 MB)
Kleesiek, J, Biller, A, Urban, G, Köthe, U, Bendszus, M and Hamprecht, F A (2014). ilastik for Multi-modal Brain Tumor Segmentation. MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, 3rdplace. 12-17PDF icon Technical Report (405.91 KB)
Kandemir, M and Hamprecht, F A (2014). Instance Label Prediction by Dirichlet Process Multiple Instance Learning. UAI. ProceedingsPDF icon Technical Report (4.26 MB)
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
Straehle, C, Kandemir, M, Köthe, U and Hamprecht, F A (2014). Multiple instance learning with response-optimized random forests. ICPR. Proceedings. 3768 - 3773PDF icon Technical Report (296.66 KB)
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
Maco, B, Cantoni, M, Holtmaat, A, Kreshuk, A, Hamprecht, F A and Knott, G (2014). Semiautomated Correlative 3D Electron Microscopy of In Vivo Imaged Axons and Dendrites. Nature Protocols. 9 1354-1366PDF icon Technical Report (2.01 MB)
Drory, A, Haubold, C, Avidan, S and Hamprecht, F A (2014). Semi-Global Matching: A Principled Derivation in Terms of Message Passing. GCPR. Proceedings. 43-53PDF icon Technical Report (2.6 MB)
Köthe, U, Herrmannsdörfer, F, Kats, I and Hamprecht, F A (2014). SimpleSTORM: a fast, self-calibrating reconstruction algorithm for localization microscopy. Histochemistry and Cell Biology. 141 613-627PDF icon Technical Report (2.29 MB)
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-analysisPDF icon Technical Report (5.27 MB)
Lou, X, Kloft, M, Rätsch, G and Hamprecht, F A (2014). Structured Learning from Cheap Data. Advanced Structured Prediction. The MIT PressPDF icon Technical Report (8.35 MB)
Fiaschi, L, Diego, F, Grosser, K - H, Schiegg, M, Köthe, U, Zlatic, M and Hamprecht, F A (2014). Tracking indistinguishable translucent objects over time using weakly supervised structured learning. CVPR. Proceedings. 2736 - 2743PDF icon Technical Report (1.47 MB)
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. 1267-1270PDF icon Technical Report (4.13 MB)

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