23 citations · 28 across the 5 of their papers we have counts for
5 papers
SIAM: Head and Brain MRI Segmentation from Few High-Quality Templates via Synthetic Training
Romain Valabregue, Ines Khemir, Eric Badinet +3
Synthetic training has recently advanced brain MRI segmentation by enabling contrast-agnostic models trained entirely on generated data. However, most existing approaches rely on h…
SMILE-UHURA Challenge -- Small Vessel Segmentation at Mesoscopic Scale from Ultra-High Resolution 7T Magnetic Resonance Angiograms
Soumick Chatterjee, Hendrik Mattern, Marc Dörner +45
The human brain receives nutrients and oxygen through an intricate network of blood vessels. Pathology affecting small vessels, at the mesoscopic scale, represents a critical vulne…
PyCellMech: A shape-based feature extraction pipeline for use in medical and biological studies
Janan Arslan, Henri Chhoa, Ines Khemir +2
Summary: Medical researchers obtain knowledge about the prevention and treatment of disability and disease using physical measurements and image data. To assist in this endeavor, f…
Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results
Kelly Payette, Céline Steger, Roxane Licandro +64
Segmentation is a critical step in analyzing the developing human fetal brain. There have been vast improvements in automatic segmentation methods in the past several years, and th…
Comprehensive analysis of synthetic learning applied to neonatal brain MRI segmentation
R Valabregue, F Girka, A Pron +2
Brain segmentation from neonatal MRI images is a very challenging task due to large changes in the shape of cerebral structures and variations in signal intensities reflecting the…