Research

We are interested in enhancement of health care system by developing robot vision and machine learning algorithms.


  • Medical image enhancement
  • Segmentation of interest regions (organs, vessels, or abnormality)
  • Interactive segmentation & Visualization
  • Classification & Pattern recognition for diseases biomarkers
  • Medical robot tracking
  • Analysis of tissue images


Medical image enhancement

"Enhancement of Perivascular Spaces using a Very Deep 3D Dense Network", PRIME Workshop, MICCAI, 2018

"Enhancement of Perivascular Spaces in 7T MR Image using Haar Transform of Non-local Cubes and Block-matching Filtering," Scientific Reports 2017.

Segmentation of interest regions (organs, vessels, or abnormality)

"3D Convolutional Neural Network with Skip Connections for WMH Segmentation," WMH Challenge, MICCAI 2017.

"Segmentation of perivascular spaces in 7T MR images using auto-context model with orientation-normalized features," NeuroImage 2016.

Interactive segmentation

"Multi-atlas based segmentation editing with interaction-guided patch selection and label fusion," IEEE Transactions on Biomedical Engineering 2016.

"Structured patch model for a unified automatic and interactive segmentation framework," Medical Image Analysis 2015.

Classification & Pattern recognition for diseases biomarkers

"Alcohol use effects on adolescent brain development revealed by simultaneously removing confounding factors, identifying morphometric patterns, and classifying individuals," Scientific Reports 2018.

"Joint Data Harmonization and Group Cardinality Constrained Classification," MICCAI, 2016.

Medical robot tracking

"Real-time Tracking of Guidewire Robot Tips using Deep Convolutional Neural Networks on Successive Localized Frames", IEEE Access, 2019

"Catheter Synthesis in X-Ray Fluoroscopy with Generative Adversarial Networks ", MICCAI PRIME workshop, 2019

Pathology image analysis

"Precise Separation of Adjacent Nuclei using a Siamese Neural Network," MICCAI, 2019.