no code implementations • 28 Mar 2024 • Pulkit Khandelwal, Michael Tran Duong, Constanza Fuentes, Amanda Denning, Winifred Trotman, Ranjit Ittyerah, Alejandra Bahena, Theresa Schuck, Marianna Gabrielyan, Karthik Prabhakaran, Daniel Ohm, Gabor Mizsei, John Robinson, Monica Munoz, John Detre, Edward Lee, David Irwin, Corey McMillan, M. Dylan Tisdall, Sandhitsu Das, David Wolk, Paul A. Yushkevich
Magnetic resonance imaging (MRI) is the standard modality to understand human brain structure and function in vivo (antemortem).
no code implementations • 9 Sep 2023 • Nikhil J. Dhinagar, Amit Singh, Saket Ozarkar, Ketaki Buwa, Sophia I. Thomopoulos, Conor Owens-Walton, Emily Laltoo, Yao-Liang Chen, Philip Cook, Corey McMillan, Chih-Chien Tsai, J-J Wang, Yih-Ru Wu, Paul M. Thompson
The resulting pre-trained models can be adapted to a range of downstream neuroimaging tasks, even when training data for the target task is limited.
1 code implementation • NeurIPS 2023 • Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro
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" for an individual.
2 code implementations • 21 Mar 2023 • Pulkit Khandelwal, Michael Tran Duong, Shokufeh Sadaghiani, Sydney Lim, Amanda Denning, Eunice Chung, Sadhana Ravikumar, Sanaz Arezoumandan, Claire Peterson, Madigan Bedard, Noah Capp, Ranjit Ittyerah, Elyse Migdal, Grace Choi, Emily Kopp, Bridget Loja, Eusha Hasan, Jiacheng Li, Alejandra Bahena, Karthik Prabhakaran, Gabor Mizsei, Marianna Gabrielyan, Theresa Schuck, Winifred Trotman, John Robinson, Daniel Ohm, Edward B. Lee, John Q. Trojanowski, Corey McMillan, Murray Grossman, David J. Irwin, John Detre, M. Dylan Tisdall, Sandhitsu R. Das, Laura E. M. Wisse, David A. Wolk, Paul A. Yushkevich
Postmortem MRI allows brain anatomy to be examined at high resolution and to link pathology measures with morphometric measurements.
no code implementations • 27 Feb 2023 • Nikhil J. Dhinagar, Conor Owens-Walton, Emily Laltoo, Christina P. Boyle, Yao-Liang Chen, Philip Cook, Corey McMillan, Chih-Chien Tsai, J-J Wang, Yih-Ru Wu, Ysbrand van der Werf, Paul M. Thompson
There is great interest in developing radiological classifiers for diagnosis, staging, and predictive modeling in progressive diseases such as Parkinson's disease (PD), a neurodegenerative disease that is difficult to detect in its early stages.
no code implementations • 28 Oct 2022 • Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro
We have recently studied covariance neural networks (VNNs) that operate on sample covariance matrices using the architecture derived from graph convolutional networks, and we showed VNNs enjoy significant advantages over traditional data analysis approaches.
1 code implementation • 31 May 2022 • Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro
Moreover, our experiments on multi-resolution datasets also demonstrate that VNNs are amenable to transferability of performance over covariance matrices of different dimensions; a feature that is infeasible for PCA-based approaches.
2 code implementations • 14 Oct 2021 • Pulkit Khandelwal, Shokufeh Sadaghiani, Michael Tran Duong, Sadhana Ravikumar, Sydney Lim, Sanaz Arezoumandan, Claire Peterson, Eunice Chung, Madigan Bedard, Noah Capp, Ranjit Ittyerah, Elyse Migdal, Grace Choi, Emily Kopp, Bridget Loja, Eusha Hasan, Jiacheng Li, Karthik Prabhakaran, Gabor Mizsei, Marianna Gabrielyan, Theresa Schuck, John Robinson, Daniel Ohm, Edward Lee, John Q. Trojanowski, Corey McMillan, Murray Grossman, David Irwin, M. Dylan Tisdall, Sandhitsu R. Das, Laura E. M. Wisse, David A. Wolk, Paul A. Yushkevich
Ex vivo MRI of the brain provides remarkable advantages over in vivo MRI for visualizing and characterizing detailed neuroanatomy.