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2015

M. Diebold, Blum, O., Gutsche, M., Wanner, S., Garbe, C. S., Baker, H., and Jähne, B., “Light-field camera design for high-accuracy depth estimation”, Videometrics, Range Imaging, and Applications XIII. 2015.

M. Diebold, Blum, O., Gutsche, M., Wanner, S., Garbe, C., Baker, H., and Jähne, B., “Light-field camera design for high-accuracy depth estimation”, in Videometrics, Range Imaging, and Applications XIII, 2015.

E. Mesarchaki, Kräuter, C., Krall, K. Ellen, Bopp, M., Helleis, F., Williams, J., and Jähne, B., “Measuring air–sea gas-exchange velocities in a large-scale annular wind–wave tank”, Ocean Sci., vol. 11, p. 121--138, 2015.

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

Technical Report (648.55 KB)

B. Antic, Büchler, U., Wahl, A. - S., Schwab, M. E., and Ommer, B., “Spatiotemporal Parsing of Motor Kinematics for Assessing Stroke Recovery”, in Medical Image Computing and Computer-Assisted Intervention, 2015.

Article (2.24 MB)

2016

S. Wolf, “Cell Tracking With Graphical Model Using Higher Order Features On Track Segments”, University of Heidelberg, 2016.

M. Baust, Weinmann, A., Wieczorek, M., Lasser, T., Storath, M., and Navab, N., “Combined Tensor Fitting and TV Regularization in Diffusion Tensor Imaging based on a Riemannian Manifold Approach”, IEEE Transactions on Medical Imaging, vol. 35, no. 8, pp. 1972–1989, 2016.

Technical Report (8.65 MB)

C. Haubold, Ales, J., Wolf, S., and Hamprecht, F. A., “A Generalized Successive Shortest Paths Solver for Tracking Dividing Targets”, ECCV. Proceedings, vol. LNCS 9911. Springer, pp. 566-582, 2016.

Technical Report (1.18 MB)

A. Biller, Badde, S., Nagel, A., Neumann, J. O., Wick, W., Hertenstein, A., Bendszus, M., Sahm, F., Benkhedah, N., and Kleesiek, J., “Improved Brain Tumor Classification by Sodium MR Imaging: Prediction of IDH Mutation Status and Tumor Progression”, American Journal of Neuroradiology, vol. 37 , pp. 66-73, 2016.

A. Stefanoiu, Weinmann, A., Storath, M., Navab, N., and Baust, M., “Joint Segmentation and Shape Regularization with a Generalized Forward Backward Algorithm”, IEEE Transactions on Image Processing, vol. 25, no. 7, pp. 3384 - 3394, 2016.

Technical Report (3.55 MB)

J. Kleesiek, Petersen, J., Döring, M., Maier-Hein, K., Köthe, U., Wick, W., Hamprecht, F. A., Bendszus, M., and Biller, A., “Virtual Raters for Reproducible and Objective Assessments in Radiology”, Nature Scientific Reports, vol. 6, 2016.

Technical Report (2.81 MB)

2017

M. Kandemir, Hamprecht, F. A., Wojek, C., and Schmidt, U., “Active machine learning for training an event classification”, Patent, Patent Number WO2017032775 A1, 2017.

M. Storath, Brandt, C., Hofmann, M., Knopp, T., Salamon, J., Weber, A., and Weinmann, A., “Edge preserving and noise reducing reconstruction for magnetic particle imaging”, IEEE Transactions on Medical Imaging, vol. 36, no. 1, pp. 74 - 85, 2017.

Technical Report (1.43 MB)

M. Storath, Rickert, D., Unser, M., and Weinmann, A., “Fast segmentation from blurred data in 3D fluorescence microscopy”, IEEE Transactions on Image Processing, vol. 26, no. 10, 2017.

M. Storath, Weinmann, A., and Unser, M., “Jump-penalized least absolute values estimation of scalar or circle-valued signals”, Information and Inference, vol. 6, no. 3, pp. 225–245, 2017.

Technical Report (3.4 MB)

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

Technical Report (3.76 MB)

M. Weiler, “Learning Steerable Filters for Rotation Equivariant Convolutional Neural Networks”, Heidelberg University, 2017.

B. Brattoli, Büchler, U., Wahl, A. - S., Schwab, M. E., and Ommer, B., “LSTM Self-Supervision for Detailed Behavior Analysis”, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.

Article (8.75 MB)

M. Kandemir, Hamprecht, F. A., Wojek, C., and Schmidt, U., “Maschinelles Lernen”, Patent, Patent Number WO2017032775A1, 2017.

Technical Report (317.04 KB)

V. Ulman, Maška, 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., Tomančák, P., Meijering, E., Muñoz-Barrutia, A., Kozubek, M., and Ortiz-de-Solorzano, C., “An Objective Comparison of Cell Tracking Algorithms”, Nature Methods, vol. 14, no. 12, pp. 1141-1152, 2017.

Technical Report (4.24 MB)

A. - S. Wahl, Büchler, U., Brändli, A., Brattoli, B., Musall, S., Kasper, H., Ineichen, B. V., Helmchen, F., Ommer, B., and Schwab, M. E., “Optogenetically stimulating the intact corticospinal tract post-stroke restores motor control through regionalized functional circuit formation”, Nature Communications, p. (ASW & UB contributed equally; BO and MES contributed equally), 2017.

2018

C. Weilbach, “Dictionary Learning with Bayesian GANs for Few-Shot Classification”, Heidelberg University, 2018.

A. - S. Wahl, Erlebach, E., Brattoli, B., Büchler, U., Kaiser, J., Ineichen, V. B., Mosberger, A. C., Schneeberger, S., Imobersteg, S., Wieckhorst, M., Stirn, M., Schroeter, A., Ommer, B., and Schwab, M. E., “Early reduced behavioral activity induced by large strokes affects the efficiency of enriched environment in rats”, Sage Journals, vol. Journal of Cerebral Blood Flow & Metabolism, 2018.

0271678x18777661.pdf (770.87 KB)

S. Haller, Swoboda, P., and Savchynskyy, B., “Exact MAP-Inference by Confining Combinatorial Search With LP Relaxation”, in Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), New Orleans, Louisiana, USA, February 2-7, 2018, 2018.

2018-02-02_aaai_dense_combilp.pdf (325.08 KB)

M. Storath and Weinmann, A., “Fast median filtering for phase or orientation data”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 3, pp. 639–652, 2018.

Technical Report (7.32 MB)

D. Fortun, Storath, M., Rickert, D., Weinmann, A., and Unser, M., “Fast Piecewise-Affine Motion Estimation Without Segmentation”, IEEE Transactions on Image Processing, vol. 27 , no. 11, pp. 5612 - 5624, 2018.

M. Weiler, Hamprecht, F. A., and Storath, M., “Learning Steerable Filters for Rotation Equivariant CNNs”, CVPR. Proceedings. pp. 849-858, 2018.

Technical Report (1.35 MB)

W. Erb, Weinmann, A., Ahlborg, M., Brandt, C., Bringout, G., Buzug, T. M., Frikel, J., Kaethner, C., Knopp, T., März, T., Möddel, M., Storath, M., and Weber, A., “Mathematical Analysis of the 1D Model and Reconstruction Schemes for Magnetic Particle Imaging”, Inverse Problems, vol. 34, no. 5, 2018.

M. Kiechle, Storath, M., Weinmann, A., and Kleinsteuber, M., “Model-based learning of local image features for unsupervised texture segmentation”, IEEE Transactions on Image Processing, vol. 27, no. 4, pp. 1994-2007, 2018.

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

S. Wolf, Pape, C., Bailoni, A., Rahaman, N., Kreshuk, A., Köthe, U., and Hamprecht, F. A., “The Mutex Watershed: Efficient, Parameter-Free Image Partitioning”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, vol. 11208 LNCS, pp. 571–587.

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