Application of independent component analysis with mixture density model to localize brain alpha activity in fMRI and EEG. - Jeong-Won Jeong; Tae-Seong Kim; Sungheon Gene Kim; Manbir Singh (Int. J. Imaging Syst. Technol., 2004)

Differentiation between glioblastomas and solitary brain metastases using diffusion tensor imaging. - Sumei Wang; Sungheon Gene Kim; Sanjeev Chawla; Ronald L. Wolf; Wei-Guo Zhang; Donald M. O'Rourke; Kevin D. Judy; Elias R. Melhem; Harish Poptani (NeuroImage, 2009)

In vivo quantification of demyelination and recovery using compartment-specific diffusion MRI metrics validated by electron microscopy. - Ileana O. Jelescu; Magdalena Zurek; Kerryanne V. Winters; Jelle Veraart; Anjali Rajaratnam; Nathanael S. Kim; James S. Babb; Timothy M. Shepherd; Dmitry S. Novikov; Sungheon Gene Kim; Els Fieremans (NeuroImage, 2016)

High-Resolution Breast Cancer Screening with Multi-View Deep Convolutional Neural Networks. - Krzysztof J. Geras; Stacey Wolfson; Sungheon Gene Kim; Linda Moy; Kyunghyun Cho (CoRR, 2017)

Breast Density Classification with Deep Convolutional Neural Networks. - Nan Wu; Krzysztof J. Geras; Yiqiu Shen; Jingyi Su; Sungheon Gene Kim; Eric Kim; Stacey Wolfson; Linda Moy; Kyunghyun Cho (ICASSP, 2018)

Globally-Aware Multiple Instance Classifier for Breast Cancer Screening. - Yiqiu Shen; Nan Wu; Jason Phang; Jungkyu Park 001; Sungheon Gene Kim; Linda Moy; Kyunghyun Cho; Krzysztof J. Geras (MLMI@MICCAI, 2019)

Screening Mammogram Classification with Prior Exams. - Jungkyu Park 001; Jason Phang; Yiqiu Shen; Nan Wu; Sungheon Gene Kim; Linda Moy; Kyunghyun Cho; Krzysztof J. Geras (CoRR, 2019)

Improving localization-based approaches for breast cancer screening exam classification. - Thibault Févry; Jason Phang; Nan Wu; Sungheon Gene Kim; Linda Moy; Kyunghyun Cho; Krzysztof J. Geras (CoRR, 2019)

Reducing false-positive biopsies with deep neural networks that utilize local and global information in screening mammograms. - Nan Wu; Zhe Huang 005; Yiqiu Shen; Jungkyu Park 001; Jason Phang; Taro Makino; Sungheon Gene Kim; Kyunghyun Cho; Laura Heacock; Linda Moy; Krzysztof J. Geras (CoRR, 2020)

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening. - Nan Wu; Jason Phang; Jungkyu Park 001; Yiqiu Shen; Zhe Huang 005; Masha Zorin; Stanislaw Jastrzebski; Thibault Févry; Joe Katsnelson; Eric Kim; Stacey Wolfson; Ujas Parikh; et al. (IEEE Trans. Medical Imaging, 2020)

A Simulation Pipeline to Generate Realistic Breast Images for Learning DCE-MRI Reconstruction. - Zhengnan Huang; Jonghyun Bae; Patricia M. Johnson; Terlika Sood; Laura Heacock; Justin Fogarty; Linda Moy; Sungheon Gene Kim; Florian Knoll (MLMIR@MICCAI, 2021)

Reducing False-Positive Biopsies using Deep Neural Networks that Utilize both Local and Global Image Context of Screening Mammograms. - Nan Wu; Zhe Huang 005; Yiqiu Shen; Jungkyu Park 001; Jason Phang; Taro Makino; Sungheon Gene Kim; Kyunghyun Cho; Laura Heacock; Linda Moy; Krzysztof J. Geras (J. Digit. Imaging, 2021)

An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization. - Yiqiu Shen; Nan Wu; Jason Phang; Jungkyu Park 001; Kangning Liu; Sudarshini Tyagi; Laura Heacock; Sungheon Gene Kim; Linda Moy; Kyunghyun Cho; Krzysztof J. Geras (Medical Image Anal., 2021)

Improving measurement of blood-brain barrier permeability with reduced scan time using deep-learning-derived capillary input function. - Jonghyun Bae; Chenyang Li 010; Arjun V. Masurkar; Yulin Ge; Sungheon Gene Kim (NeuroImage, 2023)

fastMRI Breast: A publicly available radial k-space dataset of breast dynamic contrast-enhanced MRI. - Eddy Solomon; Patricia M. Johnson; Zhengguo Tan; Radhika Tibrewala; Yvonne W. Lui; Florian Knoll; Linda Moy; Sungheon Gene Kim; Laura Heacock (CoRR, 2024)