28 citations · 44 across the 5 of their papers we have counts for
5 papers
Groupwise Registration with Physics-Informed Test-Time Adaptation on Multi-parametric Cardiac MRI
Xinqi Li, Yi Zhang, Li-Ting Huang +5
Multiparametric mapping MRI has become a viable tool for myocardial tissue characterization. However, misalignment between multiparametric maps makes pixel-wise analysis challengin…
MAGO-SP: Detection and Correction of Water-Fat Swaps in Magnitude-Only VIBE MRI
Robert Graf, Hendrik Möller, Sophie Starck +15
Volume Interpolated Breath-Hold Examination (VIBE) MRI generates images suitable for water and fat signal composition estimation. While the two-point VIBE provides water-fat-separa…
Detecting Unforeseen Data Properties with Diffusion Autoencoder Embeddings using Spine MRI data
Robert Graf, Florian Hunecke, Soeren Pohl +12
Deep learning has made significant strides in medical imaging, leveraging the use of large datasets to improve diagnostics and prognostics. However, large datasets often come with…
MRSegmentator: Multi-Modality Segmentation of 40 Classes in MRI and CT
Hartmut Häntze, Lina Xu, Christian J. Mertens +29
Purpose: To develop and evaluate a deep learning model for multi-organ segmentation of MRI scans. Materials and Methods: The model was trained on 1,200 manually annotated 3D axial…
SPINEPS -- Automatic Whole Spine Segmentation of T2-weighted MR images using a Two-Phase Approach to Multi-class Semantic and Instance Segmentation
Hendrik Möller, Robert Graf, Joachim Schmitt +16
Purpose. To present SPINEPS, an open-source deep learning approach for semantic and instance segmentation of 14 spinal structures (ten vertebra substructures, intervertebral discs,…