16 citations · 37 across the 6 of their papers we have counts for
6 papers
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…
VIBESegmentator: Full Body MRI Segmentation for the NAKO and UK Biobank
Robert Graf, Paul-Sören Platzek, Evamaria Olga Riedel +17
Objectives: To present a publicly available deep learning-based torso segmentation model that provides comprehensive voxel-wise coverage, including delineations that extend to the…
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…
Medical Image Harmonization Using Deep Learning Based Canonical Mapping: Toward Robust and Generalizable Learning in Imaging
Vishnu M. Bashyam, Jimit Doshi, Guray Erus +24
Conventional and deep learning-based methods have shown great potential in the medical imaging domain, as means for deriving diagnostic, prognostic, and predictive biomarkers, and…
Visual Subpopulation Discovery and Validation in Cohort Study Data
Shiva Alemzadeh, Tommy Hielscher, Uli Niemann +5
Epidemiology aims at identifying subpopulations of cohort participants that share common characteristics (e.g. alcohol consumption) to explain risk factors of diseases in cohort st…
Visual Analytics of Image-Centric Cohort Studies in Epidemiology
Bernhard Preim, Paul Klemm, Helwig Hauser +4
Epidemiology characterizes the influence of causes to disease and health conditions of defined populations. Cohort studies are population-based studies involving usually large numb…