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ORCIDCorey McMillan
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2020 – today
- 2024
[i9]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, John L. Robinson, Mónica Muñoz López, John A. Detre, Edward B. Lee, David J. Irwin, Corey McMillan, M. Dylan Tisdall, Sandhitsu R. Das, David A. Wolk, Paul A. Yushkevich:
Surface-based parcellation and vertex-wise analysis of ultra high-resolution ex vivo 7 tesla MRI in neurodegenerative diseases. CoRR abs/2403.19497 (2024)- 2023
- [c10]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, Paul M. Thompson:
Comparison of Anatomical and Diffusion MRI for detecting Parkinson's Disease using Deep Convolutional Neural Network. EMBC 2023: 1-6 - [c9]Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro:
Predicting Brain Age Using Transferable Covariance Neural Networks. ICASSP 2023: 1-5 - [c8]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:
Curriculum Based Multi-Task Learning for Parkinson's Disease Detection. ISBI 2023: 1-5 - [c7]Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro:
Explainable Brain Age Prediction using coVariance Neural Networks. NeurIPS 2023 - [i8]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:
Curriculum Based Multi-Task Learning for Parkinson's Disease Detection. CoRR abs/2302.13631 (2023) - [i7]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, Karthik Prabhakaran, Gabor Mizsei, Marianna Gabrielyan, Theresa Schuck, Winifred Trotman, John L. Robinson, Daniel T. Ohm, Edward B. Lee, John Q. Trojanowski, Corey McMillan, Murray Grossman, David J. Irwin, John A. Detre, M. Dylan Tisdall, Sandhitsu R. Das, Laura E. M. Wisse, David A. Wolk, Paul A. Yushkevich:
Automated deep learning segmentation of high-resolution 7 T ex vivo MRI for quantitative analysis of structure-pathology correlations in neurodegenerative diseases. CoRR abs/2303.12237 (2023) - [i6]Saurabh Sihag, Gonzalo Mateos, Corey T. McMillan, Alejandro Ribeiro:
Transferability of coVariance Neural Networks and Application to Interpretable Brain Age Prediction using Anatomical Features. CoRR abs/2305.01807 (2023) - [i5]Saurabh Sihag, Gonzalo Mateos, Corey T. McMillan, Alejandro Ribeiro:
Explainable Brain Age Prediction using coVariance Neural Networks. CoRR abs/2305.18370 (2023) - [i4]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, Yih-Ru Wu, Paul M. Thompson:
Video and Synthetic MRI Pre-training of 3D Vision Architectures for Neuroimage Analysis. CoRR abs/2309.04651 (2023) - 2022
- [c6]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, Tim J. Anderson, John C. Dalrymple-Alford, Tracy R. Melzer, Toni L. Pitcher, Reinhold Schmidt, Petra Schwingenschuh, Gaëtan Garraux, Mario Rango, Letizia Squarcina, Sarah Al-Bachari, Hedley C. A. Emsley, Johannes C. Klein, Clare E. Mackay, Michiel F. Dirkx, Rick C. Helmich, Francesca Assogna, Fabrizio Piras, Joanna K. Bright, Gianfranco Spalletta, Kathleen Poston, Christine Lochner, Corey T. McMillan, Daniel Weintraub, Jason Druzgal, Benjamin Newman, Odile A. van den Heuvel, Neda Jahanshad, Paul M. Thompson, Ysbrand D. van der Werf, Boris Gutman:
Learning Interpretable Regularized Ordinal Models from 3D Mesh Data for Neurodegenerative Disease Staging. MLCN@MICCAI 2022: 115-124 - [c5]Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro:
coVariance Neural Networks. NeurIPS 2022 - [i3]Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro:
coVariance Neural Networks. CoRR abs/2205.15856 (2022) - [i2]Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro:
Predicting Brain Age using Transferable coVariance Neural Networks. CoRR abs/2210.16363 (2022) - 2021
- [i1]Pulkit Khandelwal, Shokufeh Sadaghiani, 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 L. Robinson, Daniel T. Ohm, Edward B. Lee, John Q. Trojanowski, Corey McMillan, Murray Grossman, David J. Irwin, M. Dylan Tisdall, Sandhitsu R. Das, Laura E. M. Wisse, David A. Wolk, Paul A. Yushkevich:
Gray Matter Segmentation in Ultra High Resolution 7 Tesla ex vivo T2w MRI of Human Brain Hemispheres. CoRR abs/2110.07711 (2021)
2010 – 2019
- 2016
- [j7]Stefan Heim, Corey T. McMillan, Robin Clark, Laura Baehr, Kylie Ternes, Christopher Olm, Nam Eun Min, Murray Grossman:
How the brain learns how few are "many": An fMRI study of the flexibility of quantifier semantics. NeuroImage 125: 45-52 (2016) - 2014
- [j6]Brian B. Avants, David J. Libon, Katya Rascovsky, Ashley Boller, Corey McMillan, Lauren Massimo, H. Branch Coslett, Anjan Chatterjee, Rachel G. Gross, Murray Grossman:
Sparse canonical correlation analysis relates network-level atrophy to multivariate cognitive measures in a neurodegenerative population. NeuroImage 84: 698-711 (2014) - [j5]Philip A. Cook, Corey T. McMillan, Brian B. Avants, Jonathan E. Peelle, James C. Gee, Murray Grossman:
Relating brain anatomy and cognitive ability using a multivariate multimodal framework. NeuroImage 99: 477-486 (2014) - 2013
- [j4]Murray Grossman, Jonathan E. Peelle, Edward E. Smith, Corey McMillan, Philip A. Cook, John Powers, Michael Dreyfuss, Michael F. Bonner, Lauren L. Richmond, Ashley Boller, Emily Camp, Lisa Burkholder:
Category-specific semantic memory: Converging evidence from bold fMRI and Alzheimer's disease. NeuroImage 68: 263-274 (2013) - 2012
- [c4]Brian B. Avants, Paramveer S. Dhillon, Benjamin M. Kandel, Philip A. Cook, Corey McMillan, Murray Grossman, James C. Gee:
Eigenanatomy Improves Detection Power for Longitudinal Cortical Change. MICCAI (3) 2012: 206-213 - 2011
- [c3]Corey McMillan, Neville Ryant, Danielle Coleman, Robin Clark, Murray Grossman:
Strategic Resources Support the Interpretation of Doubly-Quantified Sentences. CogSci 2011 - 2010
- [c2]Jeffrey T. Duda, Corey McMillan, Murray Grossman, James C. Gee:
Relating Structural and Functional Connectivity to Performance in a Communication Task. MICCAI (2) 2010: 282-289 - [c1]Brian B. Avants, Philip A. Cook, Corey McMillan, Murray Grossman, Nicholas J. Tustison, Yuanjie Zheng, James C. Gee:
Sparse Unbiased Analysis of Anatomical Variance in Longitudinal Imaging. MICCAI (1) 2010: 324-331
2000 – 2009
- 2006
- [j3]Murray Grossman, Phyllis Koenig, John Kounios, Corey McMillan, Melissa Work, Peachie Moore:
Category-specific effects in semantic memory: Category-task interactions suggested by fMRI. NeuroImage 30(3): 1003-1009 (2006) - 2005
- [j2]Phyllis Koenig, Edward E. Smith, Guila Glosser, Christian Devita, Peachie Moore, Corey McMillan, James F. Geelen, Murray Grossman:
The neural basis for novel semantic categorization. NeuroImage 24(2): 369-383 (2005) - 2002
- [j1]Murray Grossman, Edward E. Smith, Phyllis Koenig, Guila Glosser, Christian Devita, Peachie Moore, Corey McMillan:
The Neural Basis for Categorization in Semantic Memory. NeuroImage 17(3): 1549-1561 (2002)
Coauthor Index
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last updated on 2024-10-07 22:09 CEST by the dblp team
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