Publications
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) Kaster, F O, Kassemeyer, S, Merkel, B, Nix, O and Hamprecht, F A (2010).
An object-oriented library for systematic training and comparison of classifiers for computer-assisted tumor diagnosis from MRSI measurements.
Bildverarbeitung für die Medizin 2010 -- Algorithmen, Systeme, Anwendungen. Springer. 97-101
Technical Report (1.12 MB) Ulman, V, 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 (2017).
An Objective Comparison of Cell Tracking Algorithms.
Nature Methods.
14 1141-1152
Technical Report (4.24 MB) 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 M
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 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) 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
L
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 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 Abstracts Technical Report (1.05 MB) Pages
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