27 citations · 47 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
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…
The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up
Razvan V. Marinescu, Neil P. Oxtoby, Alexandra L. Young +93
We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international…
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…