Gregor Köhler

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 25

Top Topics

Medical Image Segmentation

Reinforcement Learning

Unsupervised Anomaly Detection

Top Venues

Bildverarbeitung für die Medizin

IEEE Trans. Medical Imaging

Publications

Saikat Roy, Gregor Köhler, Michael Baumgartner, Constantin Ulrich, Fabian Isensee, Paul F. Jaeger, Klaus H. Maier-Hein
Abstract: 3D Medical Image Segmentation with Transformer-based Scaling of ConvNets - MedNeXt. Bildverarbeitung für die Medizin (2024)
Gregor Köhler, Tassilo Wald, Constantin Ulrich, David Zimmerer, Paul F. Jaeger, Jörg K. H. Franke, Simon Kohl, Fabian Isensee, Klaus H. Maier-Hein
Abstract: RecycleNet - Latent Feature Recycling Leads to Iterative Decision Refinement. Bildverarbeitung für die Medizin (2024)
Gregor Köhler, Tassilo Wald, Constantin Ulrich, David Zimmerer, Paul F. Jaeger, Jörg K. H. Franke, Simon Kohl, Fabian Isensee, Klaus H. Maier-Hein
RecycleNet: Latent Feature Recycling Leads to Iterative Decision Refinement. WACV (2024)
Carsten T. Lüth, David Zimmerer, Gregor Köhler, Paul F. Jaeger, Fabian Isensee, Klaus H. Maier-Hein
Contrastive Representations for Unsupervised Anomaly Detection and Localization. Bildverarbeitung für die Medizin (2023)
Jörg K. H. Franke, Michael Hefenbrock, Gregor Köhler, Frank Hutter
New Horizons in Parameter Regularization: A Constraint Approach. CoRR (2023)
Carsten T. Lüth, David Zimmerer, Gregor Köhler, Paul F. Jaeger, Fabian Isensee, Jens Petersen, Klaus H. Maier-Hein
CRADL: Contrastive Representations for Unsupervised Anomaly Detection and Localization. CoRR (2023)
Saikat Roy, Tassilo Wald, Gregor Köhler, Maximilian R. Rokuss, Nico Disch, Julius Holzschuh, David Zimmerer, Klaus H. Maier-Hein
SAM.MD: Zero-shot medical image segmentation capabilities of the Segment Anything Model. CoRR (2023)
Tassilo Wald, Constantin Ulrich, Fabian Isensee, David Zimmerer, Gregor Köhler, Michael Baumgartner, Klaus H. Maier-Hein
Exploring new ways: Enforcing representational dissimilarity to learn new features and reduce error consistency. CoRR (2023)
Saikat Roy, Gregor Köhler, Michael Baumgartner, Constantin Ulrich, Jens Petersen, Fabian Isensee, Klaus H. Maier-Hein
Transformer Utilization in Medical Image Segmentation Networks. CoRR (2023)
Saikat Roy, Gregor Köhler, Constantin Ulrich, Michael Baumgartner, Jens Petersen, Fabian Isensee, Paul F. Jäger, Klaus H. Maier-Hein
MedNeXt: Transformer-Driven Scaling of ConvNets for Medical Image Segmentation. MICCAI (4) (2023)
David Zimmerer, Peter M. Full, Fabian Isensee, Paul Jäger, Tim Adler, Jens Petersen, Gregor Köhler, Tobias Roß, Annika Reinke, Antanas Kascenas, Bjørn Sand Jensen, Alison Q. O'Neil, Jeremy Tan, Benjamin Hou, James Batten, Huaqi Qiu, Bernhard Kainz, Nina Shvetsova, Irina Fedulova, Dmitry V. Dylov, Baolun Yu, Jianyang Zhai, Jingtao Hu, Runxuan Si, Sihang Zhou, Siqi Wang, Xinyang Li, Xuerun Chen, Yang Zhao, Sergio Naval Marimont, Giacomo Tarroni, Victor Saase, Lena Maier-Hein, Klaus H. Maier-Hein
Abstract: MOOD 2020 - A Public Benchmark for Out-of-distribution Detection and Localization on Medical Images. Bildverarbeitung für die Medizin (2023)
Gregor Köhler, Tassilo Wald, Constantin Ulrich, David Zimmerer, Paul F. Jaeger, Jörg K. H. Franke, Simon Kohl, Fabian Isensee, Klaus H. Maier-Hein
RecycleNet: Latent Feature Recycling Leads to Iterative Decision Refinement. CoRR (2023)
Saikat Roy, Gregor Köhler, Constantin Ulrich, Michael Baumgartner, Jens Petersen, Fabian Isensee, Paul F. Jaeger, Klaus H. Maier-Hein
MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation. CoRR (2023)
Gregor Köhler, Fabian Isensee, Klaus H. Maier-Hein
A Noisy nnU-Net Student for Semi-supervised Abdominal Organ Segmentation. FLARE@MICCAI (2022)
David Zimmerer, Daniel Paech, Carsten Lüth, Jens Petersen, Gregor Köhler, Klaus H. Maier-Hein
Unsupervised Anomaly Detection in the Wild. Bildverarbeitung für die Medizin (2022)
David Zimmerer, Peter M. Full, Fabian Isensee, Paul Jäger, Tim Adler, Jens Petersen, Gregor Köhler, Tobias Roß, Annika Reinke, Antanas Kascenas, Bjørn Sand Jensen, Alison Q. O'Neil, Jeremy Tan, Benjamin Hou, James Batten, Huaqi Qiu, Bernhard Kainz, Nina Shvetsova, Irina Fedulova, Dmitry V. Dylov, Baolun Yu, Jianyang Zhai, Jingtao Hu, Runxuan Si, Sihang Zhou, Siqi Wang, Xinyang Li, Xuerun Chen, Yang Zhao, Sergio Naval Marimont, Giacomo Tarroni, Victor Saase, Lena Maier-Hein, Klaus H. Maier-Hein
MOOD 2020: A Public Benchmark for Out-of-Distribution Detection and Localization on Medical Images. IEEE Trans. Medical Imaging 41 (10) (2022)
Jens Petersen, Fabian Isensee, Gregor Köhler, Paul F. Jäger, David Zimmerer, Ulf Neuberger, Wolfgang Wick, Jürgen Debus, Sabine Heiland, Martin Bendszus, Philipp Vollmuth, Klaus H. Maier-Hein
Continuous-Time Deep Glioma Growth Models. CoRR (2021)
Jens Petersen, Fabian Isensee, Gregor Köhler, Paul F. Jäger, David Zimmerer, Ulf Neuberger, Wolfgang Wick, Jürgen Debus, Sabine Heiland, Martin Bendszus, Philipp Vollmuth, Klaus H. Maier-Hein
Continuous-Time Deep Glioma Growth Models. MICCAI (3) (2021)
Jens Petersen, Gregor Köhler, David Zimmerer, Fabian Isensee, Paul F. Jäger, Klaus H. Maier-Hein
GP-ConvCNP: Better generalization for conditional convolutional Neural Processes on time series data. UAI (2021)
Jörg K. H. Franke, Gregor Köhler, André Biedenkapp, Frank Hutter
Sample-Efficient Automated Deep Reinforcement Learning. ICLR (2021)
Jens Petersen, Gregor Köhler, David Zimmerer, Fabian Isensee, Paul F. Jäger, Klaus H. Maier-Hein
GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data. CoRR (2021)
Jörg K. H. Franke, Gregor Köhler, André Biedenkapp, Frank Hutter
Sample-Efficient Automated Deep Reinforcement Learning. CoRR (2020)
Jörg K. H. Franke, Gregor Köhler, Noor H. Awad, Frank Hutter
Neural Architecture Evolution in Deep Reinforcement Learning for Continuous Control. CoRR (2019)
Fabian Isensee, Jens Petersen, André Klein, David Zimmerer, Paul F. Jaeger, Simon Kohl, Jakob Wasserthal, Gregor Köhler, Tobias Norajitra, Sebastian J. Wirkert, Klaus H. Maier-Hein
Abstract: nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation. Bildverarbeitung für die Medizin (2019)
Fabian Isensee, Jens Petersen, André Klein, David Zimmerer, Paul F. Jaeger, Simon Kohl, Jakob Wasserthal, Gregor Köhler, Tobias Norajitra, Sebastian J. Wirkert, Klaus H. Maier-Hein
nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation. CoRR (2018)