J
Jens Petersen
Researcher at German Cancer Research Center
Publications - 56
Citations - 4089
Jens Petersen is an academic researcher from German Cancer Research Center. The author has contributed to research in topics: Computer science & Deep learning. The author has an hindex of 14, co-authored 41 publications receiving 1570 citations. Previous affiliations of Jens Petersen include Heidelberg University.
Papers
More filters
Journal ArticleDOI
nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation
Fabian Isensee,Fabian Isensee,Paul F. Jaeger,Simon A. A. Kohl,Jens Petersen,Jens Petersen,Klaus H. Maier-Hein,Klaus H. Maier-Hein +7 more
TL;DR: nnU-Net as mentioned in this paper is a deep learning-based segmentation method that automatically configures itself, including preprocessing, network architecture, training and post-processing for any new task.
Posted Content
nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation
Fabian Isensee,Jens Petersen,André Klein,David Zimmerer,Paul F. Jaeger,Simon A. A. Kohl,Jakob Wasserthal,Gregor Koehler,Tobias Norajitra,Sebastian J. Wirkert,Klaus H. Maier-Hein +10 more
TL;DR: The nnU-Net ('no-new-Net'), which refers to a robust and self-adapting framework on the basis of 2D and 3D vanilla U-Nets, is introduced and evaluated in the context of the Medical Segmentation Decathlon challenge.
Journal ArticleDOI
Automated Design of Deep Learning Methods for Biomedical Image Segmentation
TL;DR: Without manual tuning, nnU-Net surpasses most specialised deep learning pipelines in 19 public international competitions and sets a new state of the art in the majority of the 49 tasks, demonstrating a vast hidden potential in the systematic adaptation of deep learning methods to different datasets.
Journal ArticleDOI
Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study.
Philipp Kickingereder,Fabian Isensee,Irada Tursunova,Jens Petersen,Ulf Neuberger,David Bonekamp,Gianluca Brugnara,Marianne Schell,Tobias Kessler,Martha Foltyn,Inga Harting,Felix Sahm,Marcel Prager,Martha Nowosielski,Antje Wick,Marco Nolden,Alexander Radbruch,Jürgen Debus,Heinz Peter Schlemmer,Sabine Heiland,Michael Platten,Andreas von Deimling,Martin J. van den Bent,Thierry Gorlia,Wolfgang Wick,Martin Bendszus,Klaus H. Maier-Hein +26 more
TL;DR: In this paper, the authors developed a framework relying on artificial neural networks (ANNs) for fully automated quantitative analysis of MRI in neuro-oncology to overcome the inherent limitations of manual assessment of tumour burden and treatment response.
Book ChapterDOI
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 A. A. Kohl,Jakob Wasserthal,Gregor Koehler,Tobias Norajitra,Sebastian J. Wirkert,Klaus H. Maier-Hein +10 more
TL;DR: The U-Net was presented in 2015 and quickly evolved to a commonly used benchmark in medical image segmentation and comprises several degrees of freedom regarding the exact architecture, preprocessing, training and inference.