Heejong Kim

Postdoctoral researcher

About

My research focuses on the development of computational methods for medical image processing and analysis. I recently got my Ph.D. at NYU Visualization and Data Analytics Research Center, advised by Guido Gerig. I will join Mert Sabuncu’s group at Cornell Tech as a postdoctoral researcher this Fall and work on machine learning projects related to prostate cancer imaging.

Recent Updates

June 2021 : Our paper jointly led by Mengwei Ren learning diffusion weighted images from multi-modal structural MRI was accepted by MICCAI 2021 (Project page).
May 2021: I got my Ph.D. :)
May 2021: Our study of biochemical sensing using microparticle with OCT image and deep learning participated during my internship at Nokia Bell Lab is out in ACS NANO.
Feb 2021: Our paper led by Axel Elaldi and Neel Dey learning equivariant sparse spherical deconvolution for diffusion MRI images was accepted by IPMI 2021.
Oct 2020: I received National Institutes of Health (NIH) travel awards at MICCAI 2020.

Publications

Q-space Conditioned Translation Networks for Directional Synthesis of Diffusion Weighted Images from Multi-modal Structural MRI

M Ren^∗, H Kim^∗, N Dey, G Gerig

MICCAI: Medical Image Computing and Computer Assisted Intervention, 2021.

[ Preprint | Code | Webpage | ^∗Equal contribution ]

Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data

A Elaldi, N Dey, H Kim, G Gerig

IPMI: Information Processing in Medical Imaging, 2021.

[ Preprint | Code ]

Microparticle-based Biochemical Sensing Using Optical Coherence Tomography and Deep Learning

S Shah, CN Yu, M Zheng, H Kim, MS Eggleston

ACS Nano, 2021.

[ Paper ]

Hierarchical Geodesic Modeling on the Diffusion Orientation Distribution Function for Longitudinal DW-MRI Analysis

H Kim, S Hong, M Styner, J Piven, K Botteron, G Gerig

MICCAI: Medical Image Computing and Computer Assisted Intervention, 2020.

[ Paper ]

A framework to construct a longitudinal dw-mri infant atlas based on mixed effects modeling of dodf coefficients

H Kim, M Styner, J Piven, G Gerig

MICCAI CDMRI: Computational Diffusion MRI, 2020.

[ Paper | Oral presentation | Best oral presentation award ]

Longitudinal structural connectivity in the developing brain with projective non-negative matrix factorization

H Kim, J Piven, G Gerig

SPIE Medical Imaging, 2019.

[ Paper | Oral presentation | Best paper finalist ]

Using individualized brain network for analyzing structural covariance of the cerebral cortex in alzheimer's patients

HJ Kim, JH Shin, CE Han, HJ Kim, DL Na, SW Seo, JK Seong, and the ADNI

Frontiers in neuroscience, 2016.

[ Paper ]

Tract-specific correlates of neuropsychological deficits in patients with subcortical vascular cognitive impairment

NY Jung, CE Han, HJ Kim, SW Yoo, HJ Kim, EJ Kim, DL Na, SN Lockhart, WJ Jagust, JK Seong, SW Seo

Journal of Alzheimer's Disease, 2016.

[ Paper ]