XEdgeConv: Leveraging graph convolutions for efficient, permutation- and rotation-invariant dense 3D medical image segmentation. - Christian Weihsbach; Lasse Hansen; Mattias P. Heinrich (GeoMedIA, 2022)

DeepSTAPLE: Learning to Predict Multimodal Registration Quality for Unsupervised Domain Adaptation. - Christian Weihsbach; Alexander Bigalke; Christian N. Kruse; Hellena Hempe; Mattias P. Heinrich (WBIR, 2022)

CineJENSE: Simultaneous Cine MRI Image Reconstruction and Sensitivity Map Estimation Using Neural Representations. - Ziad Al-Haj Hemidi; Nora Vogt; Lucile Quillien; Christian Weihsbach; Mattias P. Heinrich; Julien Oster (STACOM@MICCAI, 2023)

DG-TTA: Out-of-domain medical image segmentation through Domain Generalization and Test-Time Adaptation. - Christian Weihsbach; Christian N. Kruse; Alexander Bigalke; Mattias P. Heinrich (CoRR, 2023)

IM-MoCo: Self-supervised MRI Motion Correction Using Motion-Guided Implicit Neural Representations. - Ziad Al-Haj Hemidi; Christian Weihsbach; Mattias P. Heinrich (MICCAI (7), 2024)

AcquisitionFocus: Joint Optimization of Acquisition Orientation and Cardiac Volume Reconstruction Using Deep Learning. - Christian Weihsbach; Nora Vogt; Ziad Al-Haj Hemidi; Alexander Bigalke; Lasse Hansen; Julien Oster; Mattias P. Heinrich (Sensors, 2024)

Abstract: IM-MoCo - Self-supervised MRI Motion Correction using Motion-guided Implicit Neural Representations. - Ziad Al-Haj Hemidi; Christian Weihsbach; Mattias P. Heinrich (Bildverarbeitung für die Medizin, 2025)

Autocalibration for 3D Ultrasound Reconstruction in Infant Hip Dysplasia Screening. - Wiebke Heyer; Christian Weihsbach; Christoph Otte; Jürgen Lichtenstein; Sebastian Lippross; Mattias P. Heinrich; Lasse Hansen (Bildverarbeitung für die Medizin, 2025)