activity
20192022
most citedDeepMRSeg: A convolutional deep neural network for anatomy and abnormality segmentation on MR images

27 citations · 34 across the 5 of their papers we have counts for

collaborators

6 papers

eess.IV20223 cited

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…

q-bio.NC2021

Multidimensional representations in late-life depression: convergence in neuroimaging, cognition, clinical symptomatology and genetics

Junhao Wen, Cynthia H. Y. Fu, Duygu Tosun +22

Late-life depression (LLD) is characterized by considerable heterogeneity in clinical manifestation. Unraveling such heterogeneity would aid in elucidating etiological mechanisms a…

cs.LG2021

Disentangling Alzheimer's disease neurodegeneration from typical brain aging using machine learning

Gyujoon Hwang, Ahmed Abdulkadir, Guray Erus +18

Neuroimaging biomarkers that distinguish between typical brain aging and Alzheimer's disease (AD) are valuable for determining how much each contributes to cognitive decline. Machi…

cs.LG20214 cited

Disentangling brain heterogeneity via semi-supervised deep-learning and MRI: dimensional representations of Alzheimer's Disease

Zhijian Yang, Ilya M. Nasrallah, Haochang Shou +8

Heterogeneity of brain diseases is a challenge for precision diagnosis/prognosis. We describe and validate Smile-GAN (SeMI-supervised cLustEring-Generative Adversarial Network), a…

eess.IV2020

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…

eess.IV201927 cited

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…