938 citations
- University of LausanneCH14 papers
- École Polytechnique Fédérale de LausanneCH12 papers
- Medical University of ViennaAT6 papers
- Centre Hospitalier Universitaire VaudoisCH4 papers
- Centre National de la Recherche ScientifiqueFR4 papers
- King's College LondonGB4 papers
- University Children's Hospital ZurichCH4 papers
- University of ZurichCH4 papers
- Athinoula A. Martinos Center for Biomedical ImagingUS3 papers
- Hospital Sant Joan de Déu BarcelonaES3 papers
- Boston Children's HospitalUS2 papers
- Cardiff UniversityGB2 papers
7 papers · 1 filter
Agreement of Image Quality Metrics with Radiological Evaluation in the Presence of Motion Artifacts
Elisa Marchetto, Hannah Eichhorn, Daniel Gallichan +2
Purpose: Reliable image quality assessment is crucial for evaluating new motion correction methods for magnetic resonance imaging. In this work, we compare the performance of commo…
Evaluating Synthetic Data Generation for Domain Generalization in Fetal Brain MRI Segmentation
Vladyslav Zalevskyi, Thomas Sanchez, Margaux Roulet +10
Fetal brain tissue segmentation from magnetic resonance imaging (MRI) is crucial for studying neurodevelopment, but remains challenging due to data heterogeneity and limited annota…
A diffusion MRI model for random walks confined on cylindrical surfaces: Towards non-invasive quantification of myelin sheath radius
Erick J Canales-Rodríguez, Chantal M. W. Tax, Elda Fischi-Gomez +3
Quantifying the myelin sheath radius of myelinated axons in vivo is important for understanding, diagnosing, and monitoring various neurological disorders. Despite advancements in…
WALINET: A water and lipid identification convolutional Neural Network for nuisance signal removal in 1H MR Spectroscopic Imaging
Paul Weiser, Georg Langs, Stanislav Motyka +5
Purpose. Proton Magnetic Resonance Spectroscopic Imaging (1H-MRSI) provides non-invasive spectral-spatial mapping of metabolism. However, long-standing problems in whole-brain 1H-M…
Structured Random Model for Fast and Robust Phase Retrieval
Zhiyuan Hu, Julián Tachella, Michael Unser +1
Phase retrieval, a nonlinear problem prevalent in imaging applications, has been extensively studied using random models, some of which with i.i.d. sensing matrix components. While…
Ground-truth effects in learning-based fiber orientation distribution estimation in neonatal brains
Rizhong Lin, Hamza Kebiri, Ali Gholipour +4
Diffusion Magnetic Resonance Imaging (dMRI) is a non-invasive method for depicting brain microstructure in vivo. Fiber orientation distributions (FODs) are mathematical representat…