47 citations · 89 across the 15 of their papers we have counts for
3 papers · 1 filter
Unsupervised Deep Learning for Bayesian Brain MRI Segmentation
Adrian V. Dalca, Evan Yu, Polina Golland +3
Probabilistic atlas priors have been commonly used to derive adaptive and robust brain MRI segmentation algorithms. Widely-used neuroimage analysis pipelines rely heavily on these…
Joint inference on structural and diffusion MRI for sequence-adaptive Bayesian segmentation of thalamic nuclei with probabilistic atlases
Juan Eugenio Iglesias, Koen Van Leemput, Polina Golland +1
Segmentation of structural and diffusion MRI (sMRI/dMRI) is usually performed independently in neuroimaging pipelines. However, some brain structures (e.g., globus pallidus, thalam…
Large-scale mammography CAD with Deformable Conv-Nets
Stephen Morrell, Zbigniew Wojna, Can Son Khoo +2
State-of-the-art deep learning methods for image processing are evolving into increasingly complex meta-architectures with a growing number of modules. Among them, region-based ful…