Do We Really Need Robust and Alternative Inference Methods for Brain MRI? - Bennett A. Landman; Xue Yang; Hakmook Kang (MBIA, 2012)

Quantitative Evaluation of Statistical Inference in Resting State Functional MRI. - Xue Yang; Hakmook Kang; Allen T. Newton; Bennett A. Landman (MICCAI (2), 2012)

Whole Brain Functional Connectivity Using Multi-scale Spatio-Spectral Random Effects Model. - Hakmook Kang; Xue Yang; Frederick W. Bryan; Christina M. Tripp; Bennett A. Landman (MBIA, 2013)

Functional Networks in Temporal-Lobe Epilepsy: A Voxel-Wise Study of Resting-State Functional Connectivity and Gray-Matter Concentration. - Martha J. Holmes; Xue Yang; Bennett A. Landman; Zhaohua Ding; Hakmook Kang; Bassel Abou-Khalil; Hasan H. Sonmezturk; John C. Gore; Victoria L. Morgan (Brain Connect., 2013)

Mapping mean axon diameter and axonal volume fraction by MRI using temporal diffusion spectroscopy. - Junzhong Xu; Hua Li; Kevin D. Harkins; Xiaoyu Jiang; Jingping Xie; Hakmook Kang; Mark D. Does; John C. Gore (NeuroImage, 2014)

Evaluation of Statistical Inference on Empirical Resting State fMRI. - Xue Yang; Hakmook Kang; Allen T. Newton; Bennett A. Landman (IEEE Trans. Biomed. Eng., 2014)

Revealing latent value of clinically acquired CTs of traumatic brain injury through multi-atlas segmentation in a retrospective study of 1, 003 with external cross-validation. - Andrew J. Plassard; Patrick D. Kelly; Andrew J. Asman; Hakmook Kang; Mayur B. Patel; Bennett A. Landman (Image Processing, 2015)

Simultaneous control of error rates in fMRI data analysis. - Hakmook Kang; Jeffrey Blume; Hernando Ombao; David Badre (NeuroImage, 2015)

Mapping Lifetime Brain Volumetry with Covariate-Adjusted Restricted Cubic Spline Regression from Cross-Sectional Multi-site MRI. - Yuankai Huo; Katherine Aboud; Hakmook Kang; Laurie E. Cutting; Bennett A. Landman (MICCAI (1), 2016)

A Bayesian Double Fusion Model for Resting-State Brain Connectivity Using Joint Functional and Structural Data. - Hakmook Kang; Hernando C. Ombao; Christopher Fonnesbeck; Zhaohua Ding; Victoria L. Morgan (Brain Connect., 2017)

Evaluation of inter-site bias and variance in diffusion-weighted MRI. - Allison E. Hainline; Vishwesh Nath; Prasanna Parvathaneni; Justin A. Blaber; Baxter P. Rogers; Allen T. Newton; Jeffrey Luci; Heidi Edmonson; Hakmook Kang; Bennett A. Landman (Image Processing, 2018)

Sulcal depth-based cortical shape analysis in normal healthy control and schizophrenia groups. - Ilwoo Lyu; Hakmook Kang; Neil D. Woodward; Bennett A. Landman (Image Processing, 2018)

SHARD: spherical harmonic-based robust outlier detection for HARDI methods. - Vishwesh Nath; Kurt G. Schilling; Allison E. Hainline; Prasanna Parvathaneni; Justin A. Blaber; Ilwoo Lyu; Adam W. Anderson; Hakmook Kang; Allen T. Newton; Baxter P. Rogers; Bennett A. Landman (Image Processing, 2018)

Constructing statistically unbiased cortical surface templates using feature-space covariance. - Prasanna Parvathaneni; Ilwoo Lyu; Yuankai Huo; Justin A. Blaber; Allison E. Hainline; Hakmook Kang; Neil D. Woodward; Bennett A. Landman (Image Processing, 2018)

Hierarchical spherical deformation for cortical surface registration. - Ilwoo Lyu; Hakmook Kang; Neil D. Woodward; Martin A. Styner; Bennett A. Landman (Medical Image Anal., 2019)

Quantitative magnetization transfer imaging of the human locus coeruleus. - Paula Trujillo; Kalen J. Petersen; Matthew J. Cronin; Ya-Chen Lin; Hakmook Kang; Manus J. Donahue; Seth A. Smith; Daniel O. Claassen (NeuroImage, 2019)

Electronic Medical Record Context Signatures Improve Diagnostic Classification Using Medical Image Computing. - Shikha Chaganti; Louise A. Mawn; Hakmook Kang; Josephine Egan; Susan M. Resnick; Lori L. Beason-Held; Bennett A. Landman; Thomas A. Lasko (IEEE J. Biomed. Health Informatics, 2019)

Validation of group-wise registration for surface-based functional MRI analysis. - Chang Yu 008; Yue Liu 003; Leon Y. Cai; Cailey I. Kerley; Kaiwen Xu; Warren D. Taylor; Hakmook Kang; Andrea T. Shafer; Lori L. Beason-Held; Susan M. Resnick; Bennett A. Landman; Ilwoo Lyu (Image Processing, 2021)

Graph Autoencoders for Embedding Learning in Brain Networks and Major Depressive Disorder Identification. - Fuad Noman; Chee-Ming Ting; Hakmook Kang; Raphael C.-W. Phan; Brian D. Boyd; Warren D. Taylor; Hernando C. Ombao (CoRR, 2021)

Multi-modality classification between myxofibrosarcoma and myxoma using radiomics and machine learning models. - Can Cui 006; Samuel R. Johnson; Cullen P. Moran; Katherine S. Hajdu; Joanna Shechtel; John J. Block; Brian Bingham; David Smith; Leo Y. Luo; Hakmook Kang; Jennifer L. Halpern; Herbert S. Schwartz; et al. (Computer-Aided Diagnosis, 2022)

Multimodal neuroimaging in pediatric type 1 diabetes: a pilot multisite feasibility study of acquisition quality, motion, and variability. - Leon Y. Cai; Costin Tanase; Adam W. Anderson; Karthik Ramadass; Francois Rheault; Chelsea A. Lee; Niral J. Patel; Sky Jones; Lauren M. LeStourgeon; Alix Mahon; Sumit Pruthi; Kriti Gwal; et al. (Image Processing, 2022)

Harmonization of repetition time and scanner effects on estimates of brain hemodynamic response function. - Lucie Dole; Kurt G. Schilling; Hakmook Kang; John C. Gore; Bennett A. Landman (Image Processing, 2023)

The Role of a Dopamine-Dependent Limbic-Motor Network in Sensory Motor Processing in Parkinson Disease. - Leah G. Mann; Mathieu Servant; Kaitlyn R. Hay; Alexander K. Song; Paula Trujillo; Bailu Yan; Hakmook Kang; David H. Zald; Manus J. Donahue; Gordon D. Logan; Daniel O. Claassen (J. Cogn. Neurosci., 2023)

Graph Autoencoders for Embedding Learning in Brain Networks and Major Depressive Disorder Identification. - Fuad Noman; Chee-Ming Ting; Hakmook Kang; Raphaël C.-W. Phan; Hernando C. Ombao (IEEE J. Biomed. Health Informatics, 2024)