Image processing and analysis methods for the Adolescent Brain Cognitive Development Study DJ Hagler Jr, SN Hatton, MD Cornejo, C Makowski, DA Fair, AS Dick, ... Neuroimage 202, 116091, 2019 | 726 | 2019 |
A Bayesian model for joint segmentation and registration KM Pohl, J Fisher, WEL Grimson, R Kikinis, WM Wells NeuroImage 31 (1), 228-239, 2006 | 340 | 2006 |
GLISTR: glioma image segmentation and registration A Gooya, KM Pohl, M Bilello, L Cirillo, G Biros, ER Melhem, C Davatzikos IEEE transactions on medical imaging 31 (10), 1941-1954, 2012 | 282 | 2012 |
The National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA): a multisite study of adolescent development and substance use SA Brown, TY Brumback, K Tomlinson, K Cummins, WK Thompson, ... Journal of studies on alcohol and drugs 76 (6), 895-908, 2015 | 218 | 2015 |
Altered brain developmental trajectories in adolescents after initiating drinking A Pfefferbaum, D Kwon, T Brumback, WK Thompson, K Cummins, ... American journal of psychiatry 175 (4), 370-380, 2018 | 203 | 2018 |
Neocortical gray matter volume in first-episode schizophrenia and first-episode affective psychosis: a cross-sectional and longitudinal MRI study M Nakamura, DF Salisbury, Y Hirayasu, S Bouix, KM Pohl, T Yoshida, ... Biological psychiatry 62 (7), 773-783, 2007 | 201 | 2007 |
Spatio-temporal graph convolution for resting-state fMRI analysis S Gadgil, Q Zhao, A Pfefferbaum, EV Sullivan, E Adeli, KM Pohl Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 165 | 2020 |
Adolescent development of cortical and white matter structure in the NCANDA sample: role of sex, ethnicity, puberty, and alcohol drinking A Pfefferbaum, T Rohlfing, KM Pohl, B Lane, W Chu, D Kwon, ... Cerebral cortex 26 (10), 4101-4121, 2016 | 157 | 2016 |
Training confounder-free deep learning models for medical applications Q Zhao, E Adeli, KM Pohl Nature communications 11 (1), 6010, 2020 | 149 | 2020 |
A hierarchical algorithm for MR brain image parcellation KM Pohl, S Bouix, M Nakamura, T Rohlfing, RW McCarley, R Kikinis, ... IEEE transactions on medical imaging 26 (9), 1201-1212, 2007 | 132 | 2007 |
Using the logarithm of odds to define a vector space on probabilistic atlases KM Pohl, J Fisher, S Bouix, M Shenton, RW McCarley, WEL Grimson, ... Medical Image Analysis 11 (5), 465-477, 2007 | 124 | 2007 |
White matter microstructural recovery with abstinence and decline with relapse in alcohol dependence interacts with normal ageing: a controlled longitudinal DTI study A Pfefferbaum, MJ Rosenbloom, W Chu, SA Sassoon, T Rohlfing, ... The Lancet Psychiatry 1 (3), 202-212, 2014 | 115 | 2014 |
A unifying approach to registration, segmentation, and intensity correction KM Pohl, J Fisher, JJ Levitt, ME Shenton, R Kikinis, WEL Grimson, ... Medical Image Computing and Computer-Assisted Intervention–MICCAI 2005: 8th …, 2005 | 105 | 2005 |
End-to-end Alzheimer’s disease diagnosis and biomarker identification S Esmaeilzadeh, DI Belivanis, KM Pohl, E Adeli Machine Learning in Medical Imaging: 9th International Workshop, MLMI 2018 …, 2018 | 104 | 2018 |
Image processing and analysis methods for the Adolescent Brain Cognitive Development Study. NeuroImage, 202, Article 116091 DJ Hagler Jr, S Hatton, MD Cornejo, C Makowski, DA Fair, AS Dick, ... | 101 | 2019 |
Eveningness and later sleep timing are associated with greater risk for alcohol and marijuana use in adolescence: initial findings from the national consortium on alcohol and … BP Hasler, PL Franzen, M de Zambotti, D Prouty, SA Brown, SF Tapert, ... Alcoholism: Clinical and Experimental Research 41 (6), 1154-1165, 2017 | 98 | 2017 |
Variational autoencoder for regression: Application to brain aging analysis Q Zhao, E Adeli, N Honnorat, T Leng, KM Pohl Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 92 | 2019 |
Harmonizing DTI measurements across scanners to examine the development of white matter microstructure in 803 adolescents of the NCANDA study KM Pohl, EV Sullivan, T Rohlfing, W Chu, D Kwon, BN Nichols, Y Zhang, ... Neuroimage 130, 194-213, 2016 | 90 | 2016 |
Representation learning with statistical independence to mitigate bias E Adeli, Q Zhao, A Pfefferbaum, EV Sullivan, L Fei-Fei, JC Niebles, ... Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021 | 89 | 2021 |
Joint segmentation and deformable registration of brain scans guided by a tumor growth model A Gooya, KM Pohl, M Bilello, G Biros, C Davatzikos Medical Image Computing and Computer-Assisted Intervention–MICCAI 2011: 14th …, 2011 | 88 | 2011 |