Multi-vendor and multisite evaluation of cerebrovascular reactivity mapping using hypercapnia challenge. - Peiying Liu; Dengrong Jiang; Marilyn Albert; Christopher E. Bauer; Arvind Caprihan; Brian T. Gold; Steven M. Greenberg; Karl G. Helmer; Kay Jann; Gregory Jicha; Pavel Rodriguez; Claudia L. Satizabal; et al. (NeuroImage, 2021)

Deep Learning Based Detection of Enlarged Perivascular Spaces on Brain MRI. - Tanweer Rashid; Hangfan Liu; Jeffrey B. Ware; Karl Li; Jose Rafael Romero; Elyas Fadaee; Ilya M. Nasrallah; Saima Hilal; R. Nick Bryan; Timothy M. Hughes; Christos Davatzikos; Lenore J. Launer; et al. (CoRR, 2022)

Deep Attention Assisted Multi-resolution Networks for the Segmentation of White Matter Hyperintensities in Postmortem MRI Scans. - Anoop Benet Nirmala; Tanweer Rashid; Elyas Fadaee; Nicolas Honnorat; Karl Li; Sokratis Charisis; Di Wang; Aishwarya Vemula; Jinqi Li; Peter Fox 002; Timothy E. Richardson; Jamie M. Walker; et al. (MLCN@MICCAI, 2023)

Deep neural network heatmaps capture Alzheimer's disease patterns reported in a large meta-analysis of neuroimaging studies. - Di Wang; Nicolas Honnorat; Peter T. Fox; Kerstin Ritter; Simon B. Eickhoff; Sudha Seshadri; Mohamad Habes (NeuroImage, 2023)

Riemannian frameworks for the harmonization of resting-state functional MRI scans. - Nicolas Honnorat; Sudha Seshadri; Ron Killiany; John Blangero; David C. Glahn; Peter T. Fox; Mohamad Habes (Medical Image Anal., 2024)

Rethinking the residual approach: leveraging statistical learning to operationalize cognitive resilience in Alzheimer's disease. - Colin Birkenbihl; Madison Cuppels; Rory T. Boyle; Hannah M. Klinger; Oliver Langford; Gillian T. Coughlan; Michael J. Properzi; Jasmeer P. Chhatwal; Julie C. Price; Aaron P. Schultz; Dorene M. Rentz; Rebecca E. Amariglio; et al. (Brain Informatics, 2025)