The Neural Basis for Categorization in Semantic Memory. - Murray Grossman; Edward E. Smith; Phyllis Koenig; Guila Glosser; Christian Devita; Peachie Moore; Corey McMillan (NeuroImage, 2002)

The neural basis for novel semantic categorization. - Phyllis Koenig; Edward E. Smith; Guila Glosser; Christian Devita; Peachie Moore; Corey McMillan; James F. Geelen; Murray Grossman (NeuroImage, 2005)

Category-specific effects in semantic memory: Category-task interactions suggested by fMRI. - Murray Grossman; Phyllis Koenig; John Kounios; Corey McMillan; Melissa Work; Peachie Moore (NeuroImage, 2006)

Sparse Unbiased Analysis of Anatomical Variance in Longitudinal Imaging. - Brian B. Avants; Philip A. Cook; Corey McMillan; Murray Grossman; Nicholas J. Tustison; Yuanjie Zheng; James C. Gee (MICCAI (1), 2010)

Relating Structural and Functional Connectivity to Performance in a Communication Task. - Jeffrey T. Duda; Corey McMillan; Murray Grossman; James C. Gee (MICCAI (2), 2010)

Strategic Resources Support the Interpretation of Doubly-Quantified Sentences. - Corey McMillan; Neville Ryant; Danielle Coleman; Robin Clark; Murray Grossman (CogSci, 2011)

Eigenanatomy Improves Detection Power for Longitudinal Cortical Change. - Brian B. Avants; Paramveer S. Dhillon; Benjamin M. Kandel; Philip A. Cook; Corey McMillan; Murray Grossman; James C. Gee (MICCAI (3), 2012)

Category-specific semantic memory: Converging evidence from bold fMRI and Alzheimer's disease. - Murray Grossman; Jonathan E. Peelle; Edward E. Smith; Corey McMillan; Philip A. Cook; John P. Powers; Michael Dreyfuss; Michael F. Bonner; Lauren L. Richmond; Ashley Boller; Emily Camp; Lisa Burkholder (NeuroImage, 2013)

Sparse canonical correlation analysis relates network-level atrophy to multivariate cognitive measures in a neurodegenerative population. - Brian B. Avants; David J. Libon; Katya Rascovsky; Ashley Boller; Corey McMillan; Lauren Massimo; H. Branch Coslett; Anjan Chatterjee; Rachel G. Gross; Murray Grossman (NeuroImage, 2014)

Relating brain anatomy and cognitive ability using a multivariate multimodal framework. - Philip A. Cook; Corey T. McMillan; Brian B. Avants; Jonathan E. Peelle; James C. Gee; Murray Grossman (NeuroImage, 2014)

How the brain learns how few are "many": An fMRI study of the flexibility of quantifier semantics. - Stefan Heim; Corey T. McMillan; Robin Clark; Laura Baehr; Kylie Ternes; Christopher Olm; Nam Eun Min; Murray Grossman (NeuroImage, 2016)

Gray Matter Segmentation in Ultra High Resolution 7 Tesla ex vivo T2w MRI of Human Brain Hemispheres. - Pulkit Khandelwal; Shokufeh Sadaghiani; Sadhana Ravikumar; Sydney Lim; Sanaz Arezoumandan; Claire Peterson; Eunice Chung; Madigan L. Bedard; Noah Capp; Ranjit Ittyerah; Elyse Migdal; Grace Choi; et al. (CoRR, 2021)

Learning Interpretable Regularized Ordinal Models from 3D Mesh Data for Neurodegenerative Disease Staging. - Yuji Zhao; Max A. Laansma; Eva M. van Heese; Conor Owens-Walton; Laura M. Parkes; Ines Debove; Christian Rummel; Roland Wiest; Fernando Cendes; Rachel Guimaraes; Clarissa Lin Yasuda; Jiun-Jie Wang; et al. (MLCN@MICCAI, 2022)

coVariance Neural Networks. - Saurabh Sihag; Gonzalo Mateos; Corey McMillan; Alejandro Ribeiro (NeurIPS, 2022)

Comparison of Anatomical and Diffusion MRI for detecting Parkinson's Disease using Deep Convolutional Neural Network. - Tamoghna Chattopadhyay; Amit Singh; Emily Laltoo; Christina P. Boyle; Conor Owens-Walton; Yao-Liang Chen; Philip A. Cook; Corey McMillan; Chih-Chien Tsai; Jiun-Jie Wang; Yih-Ru Wu; Ysbrand D. van der Werf; et al. (EMBC, 2023)

Predicting Brain Age Using Transferable Covariance Neural Networks. - Saurabh Sihag; Gonzalo Mateos; Corey McMillan; Alejandro Ribeiro (ICASSP, 2023)

Curriculum Based Multi-Task Learning for Parkinson's Disease Detection. - Nikhil J. Dhinagar; Conor Owens-Walton; Emily Laltoo; Christina P. Boyle; Yao-Liang Chen; Philip A. Cook; Corey McMillan; Chih-Chien Tsai; Jiun-Jie Wang; Yih-Ru Wu; Ysbrand D. van der Werf; Paul M. Thompson (ISBI, 2023)

Explainable Brain Age Prediction using coVariance Neural Networks. - Saurabh Sihag; Gonzalo Mateos; Corey McMillan; Alejandro Ribeiro (NeurIPS, 2023)

Automated deep learning segmentation of high-resolution 7 T ex vivo MRI for quantitative analysis of structure-pathology correlations in neurodegenerative diseases. - Pulkit Khandelwal; Michael Tran Duong; Shokufeh Sadaghiani; Sydney Lim; Amanda Denning; Eunice Chung; Sadhana Ravikumar; Sanaz Arezoumandan; Claire Peterson; Madigan L. Bedard; Noah Capp; Ranjit Ittyerah; et al. (CoRR, 2023)

Transferability of coVariance Neural Networks and Application to Interpretable Brain Age Prediction using Anatomical Features. - Saurabh Sihag; Gonzalo Mateos; Corey T. McMillan; Alejandro Ribeiro (CoRR, 2023)

Video and Synthetic MRI Pre-training of 3D Vision Architectures for Neuroimage Analysis. - Nikhil J. Dhinagar; Amit Singh; Saket Ozarkar; Ketaki Buwa; Sophia I. Thomopoulos; Conor Owens-Walton; Emily Laltoo; Yao-Liang Chen; Philip A. Cook; Corey McMillan; Chih-Chien Tsai; Jiun-Jie Wang; et al. (CoRR, 2023)

Surface-Based Parcellation and Vertex-wise Analysis of Ultra High-resolution ex vivo 7 tesla MRI in Alzheimer's disease and related dementias. - Pulkit Khandelwal; Michael Tran Duong; Lisa Levorse; Constanza Fuentes; Amanda Denning; Winifred Trotman; Ranjit Ittyerah; Alejandra Bahena; Theresa Schuck; Marianna Gabrielyan; Karthik Prabhakaran; Daniel T. Ohm; et al. (MLCN@MICCAI, 2024)

Surface-based parcellation and vertex-wise analysis of ultra high-resolution ex vivo 7 tesla MRI in neurodegenerative diseases. - Pulkit Khandelwal; Michael Tran Duong; Constanza Fuentes; Amanda Denning; Winifred Trotman; Ranjit Ittyerah; Alejandra Bahena; Theresa Schuck; Marianna Gabrielyan; Karthik Prabhakaran; Daniel T. Ohm; Gabor Mizsei; et al. (CoRR, 2024)