Jakob Wasserthal

According to our database, Jakob Wasserthal authored at least 12 papers between 2017 and 2023.

Collaborative distances:

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

2023

Deep Anatomical Federated Network (Dafne): an open client/server framework for the continuous collaborative improvement of deep-learning-based medical image segmentation.

Francesco Santini, Jakob Wasserthal, Abramo Agosti, Xeni Deligianni, Kevin R. Keene, Hermien E. Kan, Stefan Sommer, Christoph Stuprich, Fengdan Wang, Claudia Weidensteiner, Giulia Manco, Matteo Paoletti, Valentina Mazzoli, Arjun D. Desai, Anna Pichiecchio

CoRR, 2023

2022

TotalSegmentator: robust segmentation of 104 anatomical structures in CT images.

Jakob Wasserthal, Manfred Meyer, Hanns-Christian Breit, Joshy Cyriac, Shan Yang, Martin Segeroth

CoRR, 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

Bundle-specific tractography with machine learning.

Jakob Wasserthal

PhD thesis, 2021

2019

Combined tract segmentation and orientation mapping for bundle-specific tractography.

Jakob Wasserthal, Peter F. Neher, Dusan Hirjak, Klaus H. Maier-Hein

Medical Image Anal., 2019

Abstract: Tract Orientation Mapping for Bundle-Specific Tractography.

Jakob Wasserthal, Peter F. Neher, Klaus H. Maier-Hein

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

TractSeg - Fast and accurate white matter tract segmentation.

Jakob Wasserthal, Peter Neher, Klaus H. Maier-Hein

NeuroImage, 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

Tract Orientation Mapping for Bundle-Specific Tractography.

Jakob Wasserthal, Peter F. Neher, Klaus H. Maier-Hein

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 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

Direct White Matter Bundle Segmentation using Stacked U-Nets.

Jakob Wasserthal, Peter F. Neher, Fabian Isensee, Klaus H. Maier-Hein

CoRR, 2017