Publications

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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, in press
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 180-192PDF icon Technical Report (1.25 MB)
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 1801-1807PDF icon Technical Report (283.47 KB)
Straehle, C N, 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)
Menze, B H and Hamprecht, F A (2010). Multimodal Medical Image Analysis: from Visualization to Disease Modeling. Zeitschrift für Med. Physik. 1 1-2PDF icon Technical Report (481.58 KB)
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
Jähne, 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
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
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
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 1457-1466PDF icon Technical Report (1.45 MB)
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) 27622763PDF icon Technical Report (125.18 KB)
Staudacher, M, Hamprecht, F A and Görlitz, L (2008). Method for processing an intensity image of a microscope. Patent, Patent Number: WO2008034721A1PDF icon Technical Report (39.81 KB)
Kandemir, M, Hamprecht, F A, Wojek, C and Schmidt, U (2017). Maschinelles Lernen. Patent, Patent Number WO2017032775A1PDF icon Technical Report (317.04 KB)
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 für die Medizin. 31-36PDF icon Technical Report (672.84 KB)
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Kirschbaum, E, Haußmann, 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
Sommer, C, Fiaschi, L, Hamprecht, F A and Gerlich, D (2012). Learning-based Mitotic Cell Detection in Histopathological Images. ICPR 2012. Proceedings. 2306-2309PDF icon Technical Report (1.96 MB)
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 268-275PDF icon Technical Report (2.92 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)
Lou, X and Hamprecht, F A (2012). Learning to Segment Dense Cell Nuclei with Shape Prior. CVPR 2012. Proceedings. 1012-1018PDF icon Technical Report (2.66 MB)
Fiaschi, L, Nair, R, Köthe, U and Hamprecht, F A (2012). Learning to Count with Regression Forest and Structured Labels. ICPR 2012. Proceedings. 2685-2688PDF icon Technical Report (3.66 MB)
Weiler, M, Hamprecht, F A and Storath, M (2018). Learning Steerable Filters for Rotation Equivariant CNNs. CVPR
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)
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)
Schiegg, M, Diego, F and Hamprecht, F A (2016). Learning Diverse Models: The Coulomb Structured Support Vector Machine. ECCV. Proceedings. Springer. LNCS 9907 585-599PDF icon Technical Report (2.54 MB)
Wolf, S, Schott, L, Köthe, U and Hamprecht, F A (2017). Learned Watershed: End-to-End Learning of Seeded Segmentation. ICCV. 2030-2038PDF icon Technical Report (3.76 MB)
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/1009.4102PDF icon Technical Report (625.06 KB)
Andres, B, Kappes, J H, Beier, T, Köthe, 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_12PDF icon Technical Report (446.28 KB)

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