most citedDG-TTA: Out-of-domain Medical Image Segmentation through Augmentation and Descriptor-driven Domain Generalization and Test-Time Adaptation

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

eess.IV2024

IM-MoCo: Self-supervised MRI Motion Correction using Motion-Guided Implicit Neural Representations

Ziad Al-Haj Hemidi, Christian Weihsbach, Mattias P. Heinrich

Motion artifacts in Magnetic Resonance Imaging (MRI) arise due to relatively long acquisition times and can compromise the clinical utility of acquired images. Traditional motion c…

cs.CV2023★ 1 cited

DG-TTA: Out-of-domain Medical Image Segmentation through Augmentation and Descriptor-driven Domain Generalization and Test-Time Adaptation

Christian Weihsbach, Christian N. Kruse, Alexander Bigalke +1

Purpose: Applying pre-trained medical deep learning segmentation models on out-of-domain images often yields predictions of insufficient quality. In this study, we propose to use a…