Heejong Kim

Heejong Kim

Ph.D. Candidate

New York University

About Me

Welcome! I am a Ph.D. candidate at the NYU Visualization and Data Analytics Research Center, advised by Prof. Guido Gerig. My research focuses on development of computational methods for medical image processing and analysis.

I am currently working on

  • Longitudinal modeling for higher-order diffusion MR
  • Q-space data imputation for diffusion weighted imaging (DWI)

Interests

  • Medical image processing and analysis
  • Longitudinal modeling
  • Machine learning
  • Higher-order diffusion MRI

Education

  • PhD in Computer Science, 2021 (Expected)

    New York University

  • MEng in Bioconvergence Engineering, 2016

    Korea University

  • BEng in Biomedical Engineering, 2014

    Korea University

Recent Updates

  • National Institutes of Health (NIH) awards, MICCAI, Oct 2020
  • Best oral presentation, MICCAI CDMRI workshop in Shenzhen, Oct 2019
  • Selected intern presentation at Math & Algo team at Nokia Bell Lab, Aug 2019
  • Best student paper finalist, SPIE Medical Imaging in San Diego, Feb 2019

Recent publications

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

The analysis of anatomy that undergoes rapid changes, such as neuroimaging of the early developing brain, greatly benefits from …
Paper
Hierarchical Geodesic Modeling on the Diffusion Orientation Distribution Function for Longitudinal DW-MRI Analysis

A framework to construct a longitudinal DW-MRI infant atlas based on mixed effects modeling of dODF coefficients

Building of atlases plays a crucial role in the analysis of brain images. In scenarios where early growth, aging or disease …
Paper
A framework to construct a longitudinal DW-MRI infant atlas based on mixed effects modeling of dODF coefficients

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

Understanding of early brain changes has the potential to investigate imaging biomarkers for pre-symptomatic diagnosis and thus …
Paper
Longitudinal structural connectivity in the developing brain with projective non-negative matrix factorization
See all publications