89 citations · 150 across the 14 of their papers we have counts for
5 papers · 1 filter
Deep Learning Based Detection of Enlarged Perivascular Spaces on Brain MRI
Tanweer Rashid, Hangfan Liu, Jeffrey B. Ware +12
BACKGROUND AND PURPOSE: Deep learning has been demonstrated effective in many neuroimaging applications. However, in many scenarios, the number of imaging sequences capturing infor…
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…
A Deep Network for Joint Registration and Reconstruction of Images with Pathologies
Xu Han, Zhengyang Shen, Zhenlin Xu +5
Registration of images with pathologies is challenging due to tissue appearance changes and missing correspondences caused by the pathologies. Moreover, mass effects as observed fo…
Estimating regional cerebral blood flow using resting-state functional MRI via machine learning
Ganesh B Chand, Mohamad Habes, Sudipto Dolui +3
Perfusion MRI is an important modality in many brain imaging protocols, since it probes cerebrovascular changes in aging and many diseases; however, it may not be always available.…
DeepMRSeg: A convolutional deep neural network for anatomy and abnormality segmentation on MR images
Jimit Doshi, Guray Erus, Mohamad Habes +1
Segmentation has been a major task in neuroimaging. A large number of automated methods have been developed for segmenting healthy and diseased brain tissues. In recent years, deep…