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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

 Schütz, L M, Louveaux, M, Vilches-Barro, A, Bouziri, S, Cerrone, L, Wolny, A, Kreshuk, A, Hamprecht, F A and Maizel, A (2021). Integration of Cell Growth and Asymmetric Division during Lateral Root Initiation in Arabidopsis thaliana. Plant and Cell Physiology. 62 1269-1279

 Pape, C, Remme, R, Wolny, A, Olberg, S, Wolf, S, Cerrone, L, Cortese, M, Klaus, S, Lucic, B, Ullrich, S, Anders-Össwein, M, Wolf, S, Cerikan, B, Neufeldt, C J, Ganter, M, Schnitzler, P, Merle, U, Lusic, M, Boulant, S, Stanifer, M, Bartenschlager, R, Hamprecht, F A, Kreshuk, A, Tischer, C, Kräusslich, H - G, Müller, B and Laketa, V (2021). Microscopy-based assay for semi-quantitative detection of SARS-CoV-2 specific antibodies in human sera. BioEssays. 43

 Roth, K, Milbich, T, Ommer, B, Cohen, J Paul and Ghassemi, M (2021). S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. Proceedings of International Conference on Machine Learning (ICML). https://arxiv.org/abs/2009.08348

 Arlt, H, Sui, X, Folger, B, Adams, C, Chen, X, Remme, R, Hamprecht, F A, DiMaio, F, Liao, M, Goodman, J M, Farese, R V and Walther, T C (2021). Seipin forms a flexible cage at lipid droplet formation sites. bioRxiv

 Wolny, A, Cerrone, L, Vijayan, A, Tofanelli, R, Vilches-Barro, A, Louveaux, M, Wenzel, C, Strauss, S, Wilson-Sanchez, D, Lymbouridou, R, Steigleder, S S, Pape, C, Bailoni, A, Duran-Nebreda, S, Bassel, G W, Lohmann, J U, Tsiantis, M, Hamprecht, F A, Schneitz, K, Maizel, A and Kreshuk, A (2020). Accurate and Versatile 3D Segmentation of Plant Tissues at Cellular Resolution. eLife. 9

 Milbich, T, Roth, K, Bharadhwaj, H, Sinha, S, Bengio, Y, Ommer, B and Cohen, J Paul (2020). DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning. IEEE European Conference on Computer Vision (ECCV). https://arxiv.org/abs/2004.13458

 Roth, K, Milbich, T, Sinha, S, Gupta, P, Ommer, B and Cohen, J Paul (2020). Revisiting Training Strategies and Generalization Performance in Deep Metric Learning. International Conference on Machine Learning (ICML). https://arxiv.org/pdf/2002.08473.pdf

 Censor, Y, Petra, S and Schnörr, C (2020). Superiorization vs. Accelerated Convex Optimization: The Superiorized/Regularized Least Squares Case. J. Appl. Numer. Optimization (in press; arXiv:1911.05498). 2 15-62. http://jano.biemdas.com/archives/1060

 Jähne,  (2019). Air-Sea Gas Exchange. Encyclopedia of Ocean Sciences. Academic Press. 6 1?13

 Cerrone, L, Zeilmann, A and Hamprecht, F A (2019). End-to-End Learned Random Walker for Seeded Image Segmentation. CVPR. Proceedings. 12559-12568

 Imle, A, Kumberger, P, Schnellbächer, N D, Fehr, J, Carillo-Bustamente, P, Ales, J, Schmidt, P, Ritter, C, Godinez, W J, Müller, B, Rohr, K, Hamprecht, F A, Schwarz, U S, Graw, F and Fackler, O T (2019). Experimental and computational analyses reveal that environmental restrictions shape HIV-1 spread in 3D cultures. Nature Communications. 13;10(1)

 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, Beuttenmüller, F, Wolny, A, Zhang, C, Köthe, U, Hamprecht, F A and Kreshuk, A (2019). ilastik: interactive machine learning for (bio)image analysis. Nature Methods. 16 1226-1232

 Censor, Y, Petra, S and Schnörr, C (2019). Superiorization vs. Accelerated Convex Optimization: The Superiorized/Regularized Least Squares Case. preprint: arXiv. https://arxiv.org/abs/1911.05498

 Cerrone, L (2018). Deep End-To-End Learning Of A Diffusion Process For Seeded Image Segmentation. Heidelberg University

 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

 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

 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, Jaldén, 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, Ö, Malström, L, Jug, F, Toman?ák, P, Meijering, E, Muñoz-Barrutia, A, Kozubek, M and Ortiz-de-Solorzano, C (2017). An Objective Comparison of Cell Tracking Algorithms. Nature Methods. 14 1141-1152

 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

 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

 Censor, Y, Gibali, A, Lenzen, F and Schnörr, C (2016). The Implicit Convex Feasibility Problem and Its Application to Adaptive Image Denoising. J. Comp. Math. 34 608-623

 Zheng, S, Prisacariu, V Adrian, Averkiou, M, Cheng, M Ming, Mitra, N J, Shotton, J, Torr, P H S and Rother, C (2015). Object proposals estimation in depth image using compact 3D shape manifolds. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 9358 196?208

 Mitra, N J, Stam, J, Xu, K, Cheng, M - M, Prisacariu, V Adrian, Zheng, S, Torr, P H S and Rother, C (2015). Pacific Graphics 2015 DenseCut: Densely Connected CRFs for Realtime GrabCut. 34. http://mftp.mmcheng.net/Papers/DenseCut.pdf

 Cali, C, Baghabra, J, Boges, D J, Holst, G R, Kreshuk, A, Hamprecht, F A, Srinivasan, M, Lehväslaiho, 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

 Kiefhaber, D, Caulliez, G, Zappa, C J, Schaper, J and Jähne, B (2015). Water wave measurement from stereo images of specular reflections. 26 115401

 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

 Wahl, A - S, Omlor, W, Rubio, J C, Chen, J L, Zheng, H, Schröter, A, Gullo, M, Weinmann, O, Kobayashi, K, Helmchen, F, Ommer, B and Schwab, M E (2014). Asynchronous Therapy Restores Motor Control by Rewiring of the Rat Corticospinal Tract after Stroke. Science. American Association for The Advancement of Science. 344 1250--1255. http://www.sciencemag.org/content/344/6189/1250

 Zheng, S, Cheng, M Ming, Warrell, J, Sturgess, P, Vineet, V, Rother, C and Torr, P H S (2014). Dense semantic image segmentation with objects and attributes. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 3214?3221. http://www.robots.ox.ac.uk/?tvg/http://tu-dresden.de/inf/cvld

 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

 Goldlücke, B, Aubry, M, Kolev, K and Cremers, D (2014). A super-resolution framework for high-accuracy multiview reconstruction. Int. J. Comp. Vision. 106 172--191

 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)

 Lefloch, D, Nair, R, Lenzen, F, Schäfer, H, Streeter, L and Cree, M J (2013). Technical Foundation and Calibration Methods for Time-of-Flight Cameras. Time-of-Flight Imaging: Algorithms, Sensors and Applications. Springer. 8200

 Lefloch, D, Nair, R, Lenzen, F, Schäfer, H, Streeter, L, Cree, M J, Koch, R and Kolb, A (2013). Technical Foundation and Calibration Methods for Time-of-Flight Cameras. Time-of-Flight and Depth Imaging: Sensors, Algorithms, and Applications. Springer. 8200 3-24

 Goldlücke, B, Strekalovskiy, E and Cremers, D (2013). Tight convex relaxations for vector-valued labeling. SIAM Journal on Imaging Sciences

 Yarlagadda, P, Monroy, A, Carque, B and Ommer, B (2013). Towards a Computer-based Understanding of Medieval Images. Scientific Computing & Cultural Heritage. Springer. 89--97. http://link.springer.com/chapter/10.1007/978-3-642-28021-4_10

 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

 Goldlücke, B, Strekalovskiy, E and Cremers, D (2012). The Natural Vectorial Total Variation which Arises from GeometricMeasure Theory. SIAM Journal on Imaging Sciences. 5 537-563

 Goldlücke, B, Strekalovskiy, E and Cremers, D (2012). The natural vectorial total variation which arises from geometric measure theory. SIAM Journal on Imaging Sciences

 Kreshuk, A, Straehle, C N, Sommer, C, Köthe, 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)

 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

 Schlecht, J, Carque, B and Ommer, B (2011). Detecting Gestures in Medieval Images. Proceedings of the International Conference on Image Processing. IEEE. 1309--1312

 Töppe, E, Oswald, M R, Cremers, D and Rother, C (2011). Image-based 3D modeling via cheeger sets. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6492 LNCS 53?64

 Monroy, A, Carque, B and Ommer, B (2011). Reconstructing the Drawing Process of Reproductions from Medieval Images. Proceedings of the International Conference on Image Processing. IEEE. 2974--2977. https://hciweb.iwr.uni-heidelberg.de/compvis/research/manesse/

 Yarlagadda, P, Monroy, A, Carque, B and Ommer, B (2011). Top-down Analysis of Low-level Object Relatedness Leading to Semantic Understanding of Medieval Image Collections. Conference on Computer Vision and Image Analysis of Art II. 7869 61--69

 Gulshan, V, Rother, C, Criminisi, A, Blake, A and Zisserman, A (2010). Geodesic star convexity for interactive image segmentation. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 3129?3136

 Lin, Z, Erz, M and Jähne, B (2010). Multi-frequency multi-sampling fluorescence lifetime imaging using a high-speed line-scan camera. Optics, Photonics, and Digital Technologies for Multimedia Applications, 12--15 April 2010, Brussels. 7723 77231S

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 Yarlagadda, P, Monroy, A, Carque, B and Ommer, B (2010). Recognition and Analysis of Objects in Medieval Images. Proceedins of the Aian Conference on Computer Vision, Workshop on e-Heritage. Springer. 296--305

 Berthe, A, Kondermann, D, Christensen, C, Goubergrits, L, Garbe, C S, Affeld, K and Kertzscher, U (2010). Three-dimensional, three-component wall-PIV. Exp. Fluids. 48 online

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 Breitenreicher, D and Schnörr, C (2009). Intrinsic Second-Order Geometric Optimization for Robust Point Set Registration Without Correspondence. Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2009). Springer. 5681 274-287. http://www.springerlink.com/content/1470n7577713069q/

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 Friedrich, O, Weber, C, Both, M, von Wegner, F, Chamberlain, J S, Garbe, C S and Fink, R H A (2008). Sarcomere Structure and Motor-Protein Function in an Animal Model of Duchenne Muscular Dystrophy (mdx mouse). 87th Annual Meeting of the German Physiological Society

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 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

 Cremers, D, Sochen, N and Schnörr, C (2006). Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation. ijcv. 66 67-81

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 (2005). Variational, Geometric and Level Sets in Computer Vision (VLSM'05). lncs. Springer, Beijing, China. 3752

 Bergtholdt, M, Cremers, D and Schnörr, C (2005). Variational Segmentation with Shape Priors. Handbook of Mathematical Models in Computer Vision. Springer. 147-160

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 Scholes, M C, Matrai, P A, Andreae, M O, Smith, K A, Manning, M R, Artaxo, P, Barrie, L A, Bates, T S, Butler, J H, Ciccioli, P, Cieslik, S A, Delmas, R J and Dentener, F J (2003). Biosphere-Atmosphere Interactions. Atmospheric Chemistry in a Changing World, An Integration and Synthesis of a Decade of Tropospheric Chemistry Research. Springer. 19--71

 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

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 Cremers, D, Tischhäuser, F, Weickert, J and Schnörr, C (2002). Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford?Shah functional. Int. J. Computer Vision. 50 295?313

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 Cremers, D and Schnörr, C (2002). Motion Competition: Variational Integration of Motion Segmentation and Shape Regularization. Pattern Recognition, Proc. 24th DAGM Symposium. Springer, Zürich, Switzerland. 2449 472?480

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 Rother, C, Carlsson, S and Tell, D (2002). Projective factorization of planes and cameras in multiple views. Proceedings - International Conference on Pattern Recognition. 16 737?740

 Keuchel, J, Schnörr, C, Schellewald, C and Cremers, D (2002). Unsupervised Image Partitioning with Semidefinite Programming. Pattern Recognition, Proc. 24th DAGM Symposium. Springer, Zürich, Switzerland. 2449 141?149

 Keuchel, J, Schellewald, C, Cremers, D and Schnörr, C (2001). Convex Relaxations for Binary Image Partitioning and Perceptual Grouping. Mustererkennung 2001. Springer, Munich, Germany. 2191 353?360

 Cremers, D, Schnörr, C and Weickert, J (2001). Diffusion?Snakes: Combining Statistical Shape Knowledge and Image Information in a Variational Framework. IEEE First Workshop on Variational and Level Set Methods in Computer Vision. IEEE Comp. Soc., Vancouver, Canada. 237?244

 Heiler, M, Cremers, D and Schnörr, C (2001). Efficient Feature Subset Selection For Support Vector Machines. Dept. Math. and Comp. Science, University of Mannheim, Germany

 Rother, C and Carlsson, S (2001). Linear multi view reconstruction and camera recovery. Proceedings of the IEEE International Conference on Computer Vision. 1 42?49

 Cremers, D, Kohlberger, T and Schnörr, C (2001). Nonlinear Shape Statistics via Kernel Spaces. Mustererkennung 2001. Springer. 2191 269--276

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 Hamprecht, F A, Jost, D, Rüttimann, M, Calamai, F and Kowalski, J J (2001). Preliminary results on the prediction of countershock success with fibrillation power. Resuscitation. 50 297-299

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