641 citations · 1.2k across the 16 of their papers we have counts for
16 papers
Benchmarking of Deep Learning Methods for Generic MRI Multi-Organ Abdominal Segmentation
Deepa Krishnaswamy, Cosmin Ciausu, Steve Pieper +3
Recent advances in deep learning have led to robust automated tools for segmentation of abdominal computed tomography (CT). Meanwhile, segmentation of magnetic resonance imaging (M…
A Contrast-Agnostic Method for Ultra-High Resolution Claustrum Segmentation
Chiara Mauri, Ryan Fritz, Jocelyn Mora +5
The claustrum is a band-like gray matter structure located between putamen and insula whose exact functions are still actively researched. Its sheet-like structure makes it barely…
Learning General-Purpose Biomedical Volume Representations using Randomized Synthesis
Neel Dey, Benjamin Billot, Hallee E. Wong +5
Current volumetric biomedical foundation models struggle to generalize as public 3D datasets are small and do not cover the broad diversity of medical procedures, conditions, anato…
Towards Automatic Abdominal MRI Organ Segmentation: Leveraging Synthesized Data Generated From CT Labels
Cosmin Ciausu, Deepa Krishnaswamy, Benjamin Billot +3
Deep learning has shown great promise in the ability to automatically annotate organs in magnetic resonance imaging (MRI) scans, for example, of the brain. However, despite advance…
SE(3)-Equivariant and Noise-Invariant 3D Rigid Motion Tracking in Brain MRI
Benjamin Billot, Neel Dey, Daniel Moyer +5
Rigid motion tracking is paramount in many medical imaging applications where movements need to be detected, corrected, or accounted for. Modern strategies rely on convolutional ne…
Quantifying white matter hyperintensity and brain volumes in heterogeneous clinical and low-field portable MRI
Pablo Laso, Stefano Cerri, Annabel Sorby-Adams +21
Brain atrophy and white matter hyperintensity (WMH) are critical neuroimaging features for ascertaining brain injury in cerebrovascular disease and multiple sclerosis. Automated se…