activity
20162023
most citedBrain network efficiency is influenced by pathological source of corticobasal syndrome

4 citations · 6 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2023

Transferability of coVariance Neural Networks and Application to Interpretable Brain Age Prediction using Anatomical Features

Saurabh Sihag, Gonzalo Mateos, Corey T. McMillan +1

Graph convolutional networks (GCN) leverage topology-driven graph convolutional operations to combine information across the graph for inference tasks. In our recent work, we have…

q-bio.QM2023★ 1 cited

Explainable Brain Age Prediction using coVariance Neural Networks

Saurabh Sihag, Gonzalo Mateos, Corey McMillan +1

In computational neuroscience, there has been an increased interest in developing machine learning algorithms that leverage brain imaging data to provide estimates of "brain age" f…

cs.CV2023

Automated deep learning segmentation of high-resolution 7 T postmortem MRI for quantitative analysis of structure-pathology correlations in neurodegenerative diseases

Pulkit Khandelwal, Michael Tran Duong, Shokufeh Sadaghiani +34

Postmortem MRI allows brain anatomy to be examined at high resolution and to link pathology measures with morphometric measurements. However, automated segmentation methods for bra…

eess.IV2023

Curriculum Based Multi-Task Learning for Parkinson's Disease Detection

Nikhil J. Dhinagar, Conor Owens-Walton, Emily Laltoo +9

There is great interest in developing radiological classifiers for diagnosis, staging, and predictive modeling in progressive diseases such as Parkinson's disease (PD), a neurodege…

cs.LG2022★ 1 cited

Predicting Brain Age using Transferable coVariance Neural Networks

Saurabh Sihag, Gonzalo Mateos, Corey McMillan +1

The deviation between chronological age and biological age is a well-recognized biomarker associated with cognitive decline and neurodegeneration. Age-related and pathology-driven…

cs.LG2022

coVariance Neural Networks

Saurabh Sihag, Gonzalo Mateos, Corey McMillan +1

Graph neural networks (GNN) are an effective framework that exploit inter-relationships within graph-structured data for learning. Principal component analysis (PCA) involves the p…

eess.IV2021

Gray Matter Segmentation in Ultra High Resolution 7 Tesla ex vivo T2w MRI of Human Brain Hemispheres

Pulkit Khandelwal, Shokufeh Sadaghiani, Michael Tran Duong +30

Ex vivo MRI of the brain provides remarkable advantages over in vivo MRI for visualizing and characterizing detailed neuroanatomy. However, automated cortical segmentation methods…

q-bio.NC2016★ 4 cited

Brain network efficiency is influenced by pathological source of corticobasal syndrome

John D. Medaglia, Weiyu Huang, Santiago Segarra +6

Multimodal neuroimaging studies of corticobasal syndrome using volumetric MRI and DTI successfully discriminate between Alzheimer's disease and frontotemporal lobar degeneration bu…