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L

Andres, B, Kappes, J H, Köthe, 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

Technical Report (625.06 KB)

Wolf, S, Schott, L, Köthe, U and Hamprecht, F A (2017). Learned Watershed: End-to-End Learning of Seeded Segmentation. ICCV. 2030-2038

Technical Report (3.76 MB)

Fiaschi, L, Nair, R, Köthe, U and Hamprecht, F A (2012). Learning to Count with Regression Forest and Structured Labels. ICPR 2012. Proceedings. 2685-2688

Technical Report (3.66 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 419-427

Technical Report (2.87 MB)

M

Beier, T, Pape, C, Rahaman, N, Prange, T, Berg, S, Bock, D, Cardona, A, Knott, G W, Plaza, S M, Scheffer, L K, Köthe, 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

Straehle, C N, Kandemir, M, Köthe, U and Hamprecht, F A (2014). Multiple instance learning with response-optimized random forests. ICPR. Proceedings. 3768 - 3773

Technical Report (296.66 KB)

Hanselmann, M, Köthe, 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

Technical Report (1.25 MB)

Wolf, S, Pape, C, Bailoni, A, Rahaman, N, Kreshuk, A, Köthe, U and Hamprecht, F A (2018). The Mutex Watershed: Efficient, Parameter-Free Image Partitioning. ECCV. Proceedings. Springer. 571-587

Wolf, S, Pape, C, Bailoni, A, Rahaman, N, Kreshuk, A, Köthe, 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

N

Krasowki, N, Beier, T, Knott, G W, Köthe, U, Hamprecht, F A and Kreshuk, A (2017). Neuron Segmentation with High-Level Biological Priors. IEEE Transactions on Medical Imaging. 37

O

Menze, B H, Kelm, B Michael, Splitthoff, N, Köthe, 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

Technical Report (665.33 KB)

Adler, T J, Ayala, L, Ardizzone, L, Kenngott, H G, Vemuri, A, Müller-Stich, B P, Rother, C, Köthe, U and Maier-Hein, L (2019). Out of Distribution Detection for Intra-operative Functional Imaging. MICCAI UNSURE Workshop 2019. 11840 LNCS 75–82

PDF (3.1 MB)

P

Meine, H, Köthe, U and Stelldinger, P (2009). Pixel Approximation Errors in Common Watershed Algorithms. Discrete Geometry for Computer Imagery. Springer. 5810 193-202

Technical Report (6.5 MB)

Meine, H, Köthe, U and Stelldinger, P (2009). Pixel Approximation Errors in Common Watershed Algorithms. Discrete Geometry for Computer Imagery. Springer. 5810 193-202

Andres, B, Kappes, J H, Beier, T, Köthe, U and Hamprecht, F A (2011). Probabilistic Image Segmentation with Closedness Constraints. Proceedings of ICCV

Andres, B, Kappes, J H, Beier, T, Köthe, U and Hamprecht, F A (2011). Probabilistic Image Segmentation with Closedness Constraints. ICCV, Proceedings. 2611 - 2618

Technical Report (8.18 MB)

Andres, B, Kappes, J H, Beier, T, Köthe, U and Hamprecht, F A (2011). Probabilistic Image Segmentation with Closedness Constraints. Proceedings of ICCV

Technical Report (2.95 MB)

Schiegg, M, Heuer, B, Haubold, C, Wolf, S, Köthe, U and Hamprecht, F A (2015). Proof-reading Guidance in Cell Tracking by Sampling from Tracking-by-assignment Models. ISBI. Proceedings. 394-398

Technical Report (648.55 KB)

Q

Lou, X, Fiaschi, L, Köthe, U and Hamprecht, F A (2012). Quality Classification of Microscopic Imagery with Weakly Supervised Learning. MICCAI-MLMI. Proceedings. 176-183

Technical Report (4.15 MB)

Andres, B, Köthe, 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

Technical Report (3.08 MB)

R

Köthe, (2008). Reliable Low-Level Image Analysis. Habilitation thesis. Department Informatik, University of Hamburg, Hamburg

Technical Report (12.44 MB)

Andres, B, Köthe, U, Kröger, 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

Technical Report (415.54 KB)

S

Straehle, C N, Köthe, U, Briggman, K, Denk, W and Hamprecht, F A (2012). Seeded watershed cut uncertainty estimators for guided interactive segmentation. CVPR 2012. Proceedings. 765 - 772

Technical Report (2.84 MB)

Andres, B, Köthe, 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

Technical Report (1.21 MB)

Haubold, C, Schiegg, M, Kreshuk, A, Berg, S, Köthe, U and Hamprecht, F A (2016). Segmenting and Tracking Multiple Dividing Targets Using ilastik. Focus on Bio-Image Informatics. Springer. 219 199-229

Technical Report (4.46 MB)

Hanselmann, M, Voss, B, Renard, B Y, Lindner, M, Köthe, U, Kirchner, M and Hamprecht, F A (2011). SIMA: Simultaneous Multiple Alignment of LC/MS Peak Lists. Bioinformatics. 27 (7) 987-993

Technical Report (2.2 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. 141 613-627

Technical Report (2.29 MB)

T

Frank, M, Plaue, M, Rapp, H, Köthe, U, Jähne, B and Hamprecht, F A (2009). Theoretical and Experimental Error Analysis of Continuous-Wave Time-Of-Flight Range Cameras. Optical Engineering. 48, 013602

Technical Report (2.03 MB)

Frank, M, Plaue, M, Rapp, H, Köthe, U, Jähne, B and Hamprecht, F A (2009). Theoretical and experimental error analysis of continuous-wave time-of-flight range cameras. Opt. Eng. 48 013602

Meine, H, Köthe, U and Stelldinger, P (2008). A Topological Sampling Theorem for Robust Boundary Reconstruction and Image Segmentation. Discrete Applied Mathematics. 157 524-541

Hanselmann, M, Köthe, 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

Technical Report (1.47 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 - 2743

Technical Report (1.47 MB)

V

Kleesiek, J, Petersen, J, Döring, M, Maier-Hein, K, Köthe, 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

Technical Report (2.81 MB)

W

Straehle, C N, Köthe, U and Hamprecht, F A (2013). Weakly supervised learning of image partitioning using decision trees with structured split criteria. ICCV 2013. Proceedings. 1849-1856

Technical Report (5.97 MB)

Köthe, (2008). What Can We Learn from Discrete Images about the Continuous World. Discrete Geometry for Computer Imagery. Springer. 4992 4-19

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