David Zimmerer

According to our database, David Zimmerer authored at least 29 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Leveraging Foundation Models for Content-Based Medical Image Retrieval in Radiology.

Stefan Denner, David Zimmerer, Dimitrios Bounias, Markus Bujotzek, Shuhan Xiao, Lisa Kausch, Philipp Schader, Tobias Penzkofer, Paul F. Jäger, Klaus H. Maier-Hein

CoRR, 2024

RecycleNet: Latent Feature Recycling Leads to Iterative Decision Refinement.

Gregor Köhler, Tassilo Wald, Constantin Ulrich, David Zimmerer, Paul F. Jaeger, Jörg K. H. Franke, Simon Kohl, Fabian Isensee, Klaus H. Maier-Hein

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Abstract: RecycleNet - Latent Feature Recycling Leads to Iterative Decision Refinement.

Gregor Köhler, Tassilo Wald, Constantin Ulrich, David Zimmerer, Paul F. Jaeger, Jörg K. H. Franke, Simon Kohl, Fabian Isensee, Klaus H. Maier-Hein

Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

2023

Exploring new ways: Enforcing representational dissimilarity to learn new features and reduce error consistency.

Tassilo Wald, Constantin Ulrich, Fabian Isensee, David Zimmerer, Gregor Köhler, Michael Baumgartner, Klaus H. Maier-Hein

CoRR, 2023

SAM.MD: Zero-shot medical image segmentation capabilities of the Segment Anything Model.

Saikat Roy, Tassilo Wald, Gregor Köhler, Maximilian R. Rokuss, Nico Disch, Julius Holzschuh, David Zimmerer, Klaus H. Maier-Hein

CoRR, 2023

CRADL: Contrastive Representations for Unsupervised Anomaly Detection and Localization.

Carsten T. Lüth, David Zimmerer, Gregor Köhler, Paul F. Jaeger, Fabian Isensee, Jens Petersen, Klaus H. Maier-Hein

CoRR, 2023

Why is the Winner the Best?

Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Fabian Isensee, Tim J. Adler, Sharib Ali, Vincent Andrearczyk, Marc Aubreville, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Veronika Cheplygina, Marie Daum, Marleen de Bruijne, Adrien Depeursinge, Reuben Dorent, Jan Egger, David G. Ellis, Sandy Engelhardt, Melanie Ganz, Noha M. Ghatwary, Gabriel Girard, Patrick Godau, Anubha Gupta, Lasse Hansen, Kanako Harada, Mattias P. Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Pierre Jannin, A. Emre Kavur, Oldrich Kodym, Michal Kozubek, Jianning Li, Hongwei Bran Li, Jun Ma, Carlos Martín-Isla, Bjoern H. Menze, J. Alison Noble, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Tim Rädsch, Jonathan Rafael-Patino, Vivek Singh Bawa, Stefanie Speidel, Carole H. Sudre, Kimberlin M. H. van Wijnen, Martin Wagner, D. Wei, Amine Yamlahi, Moi Hoon Yap, C. Yuan, Maximilian Zenk, A. Zia, David Zimmerer, Dogu Baran Aydogan, Binod Bhattarai, Louise Bloch, Raphael Brüngel, J. Cho, C. Choi, Q. Dou, Ivan Ezhov, Christoph M. Friedrich, C. Fuller, Rebati Raman Gaire, Adrian Galdran, Álvaro García-Faura, Maria Grammatikopoulou, S. Hong, Mostafa Jahanifar, I. Jang, Abdolrahim Kadkhodamohammadi, I. Kang, Florian Kofler, S. Kondo, Hugo Jaco Kuijf, M. Li, M. Luu, Tomaz Martincic, Pedro Morais, Mohamed A. Naser, Bruno Oliveira, David Owen, S. Pang, J. Park, S. Park, Szymon Plotka, Élodie Puybareau, Nasir M. Rajpoot, K. Ryu, Numan Saeed, Adam Shephard, Pengcheng Shi, Dejan Stepec, Ronast Subedi, Guillaume Tochon, Helena R. Torres, Hélène Urien, João L. Vilaça, Kareem A. Wahid, H. Wang, J. Wang, L. Wang, X. Wang, Benedikt Wiestler, Marek Wodzinski, F. Xia, J. Xie, Z. Xiong, S. Yang, Y. Yang, Z. Zhao, Klaus H. Maier-Hein, Paul F. Jäger, Annette Kopp-Schneider, Lena Maier-Hein

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Abstract: MOOD 2020 - A Public Benchmark for Out-of-distribution Detection and Localization on Medical Images.

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

Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

Contrastive Representations for Unsupervised Anomaly Detection and Localization.

Carsten T. Lüth, David Zimmerer, Gregor Köhler, Paul F. Jaeger, Fabian Isensee, Klaus H. Maier-Hein

Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

2022

Unsupervised Learning for Anomaly Detection in Medical Images.

David Zimmerer

PhD thesis, 2022

MOOD 2020: A Public Benchmark for Out-of-Distribution Detection and Localization on Medical Images.

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

IEEE Trans. Medical Imaging, 2022

Unsupervised Anomaly Detection in the Wild.

David Zimmerer, Daniel Paech, Carsten T. Lüth, Jens Petersen, Gregor Köhler, Klaus H. Maier-Hein

Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

Realistic Evaluation of FixMatch on Imbalanced Medical Image Classification Tasks.

Maximilian Zenk, David Zimmerer, Fabian Isensee, Paul F. Jäger, Jakob Wasserthal, Klaus H. Maier-Hein

Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

2021

GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data.

Jens Petersen, Gregor Köhler, David Zimmerer, Fabian Isensee, Paul F. Jäger, Klaus H. Maier-Hein

CoRR, 2021

The Federated Tumor Segmentation (FeTS) Challenge.

Sarthak Pati, Ujjwal Baid, Maximilian Zenk, Brandon Edwards, Micah J. Sheller, G. Anthony Reina, Patrick Foley, Alexey Gruzdev, Jason Martin, Shadi Albarqouni, Yong Chen, Russell Taki Shinohara, Annika Reinke, David Zimmerer, John B. Freymann, Justin S. Kirby, Christos Davatzikos, Rivka R. Colen, Aikaterini Kotrotsou, Daniel S. Marcus, Mikhail Milchenko, Arash Nazeri, Hassan M. Fathallah-Shaykh, Roland Wiest, András Jakab, Marc-André Weber, Abhishek Mahajan, Lena Maier-Hein, Jens Kleesiek, Bjoern H. Menze, Klaus H. Maier-Hein, Spyridon Bakas

CoRR, 2021

GP-ConvCNP: Better generalization for conditional convolutional Neural Processes on time series data.

Jens Petersen, Gregor Köhler, David Zimmerer, Fabian Isensee, Paul F. Jäger, Klaus H. Maier-Hein

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Continuous-Time Deep Glioma Growth Models.

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

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

2020

Abstract: Unsupervised Anomaly Localization Using Variational Auto-Encoders.

David Zimmerer, Fabian Isensee, Jens Petersen, Simon Kohl, Klaus H. Maier-Hein

Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

2019

A Case for the Score: Identifying Image Anomalies using Variational Autoencoder Gradients.

David Zimmerer, Jens Petersen, Simon A. A. Kohl, Klaus H. Maier-Hein

CoRR, 2019

High- and Low-level image component decomposition using VAEs for improved reconstruction and anomaly detection.

David Zimmerer, Jens Petersen, Klaus H. Maier-Hein

CoRR, 2019

Unsupervised Anomaly Localization Using Variational Auto-Encoders.

David Zimmerer, Fabian Isensee, Jens Petersen, Simon Kohl, Klaus H. Maier-Hein

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Abstract: nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation.

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

Proceedings of the Bildverarbeitung für die Medizin 2019 - Algorithmen - Systeme, 2019

2018

Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection.

David Zimmerer, Simon A. A. Kohl, Jens Petersen, Fabian Isensee, Klaus H. Maier-Hein

CoRR, 2018

nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation.

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

CoRR, 2018

Exploiting the potential of unlabeled endoscopic video data with self-supervised learning.

Tobias Roß, David Zimmerer, Anant Suraj Vemuri, Fabian Isensee, Manuel Wiesenfarth, Sebastian Bodenstedt, Fabian Both, Philip Kessler, Martin Wagner, Beat Müller, Hannes Kenngott, Stefanie Speidel, Annette Kopp-Schneider, Klaus H. Maier-Hein, Lena Maier-Hein

Int. J. Comput. Assist. Radiol. Surg., 2018

Advanced Deep Learning Methods.

Paul Jäger, Fabian Isensee, Jens Petersen, David Zimmerer, Jakob Wasserthal, Klaus Hermann Maier-Hein

Proceedings of the Bildverarbeitung für die Medizin 2018 - Algorithmen - Systeme, 2018

2017

Exploiting the potential of unlabeled endoscopic video data with self-supervised learning.

Tobias Roß, David Zimmerer, Anant Suraj Vemuri, Fabian Isensee, Sebastian Bodenstedt, Fabian Both, Philip Kessler, Martin Wagner, Beat Müller, Hannes Kenngott, Stefanie Speidel, Klaus H. Maier-Hein, Lena Maier-Hein

CoRR, 2017

Spiking Convolutional Deep Belief Networks.

Jacques Kaiser, David Zimmerer, Juan Camilo Vasquez Tieck, Stefan Ulbrich, Arne Roennau, Rüdiger Dillmann

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017

2016

Robust environment perception for the Audi Autonomous Driving Cup.

Florian Kuhnt, Micha Pfeiffer, Peter Zimmer, David Zimmerer, Jan-Markus Gomer, Vitali Kaiser, Ralf Kohlhaas, J. Marius Zöllner

Proceedings of the 19th IEEE International Conference on Intelligent Transportation Systems, 2016