Seung-Jun Hwang
Papers
1
Total Citations
26
H-Index
1
About
Dr. Seung-Jun Hwang is a leading researcher in medical computer vision, with a primary focus on advancing endoscopic imaging and surgical assistance systems. His work centers on developing deep learning techniques for monocular depth estimation and real-time 3D reconstruction in colonoscopy, directly addressing critical challenges in colorectal cancer screening. His most cited paper, "Unsupervised Monocular Depth Estimation for Colonoscope System Using Feedback Network" (2021, 26 citations), introduces a novel feedback network that enables unsupervised learning of depth from single-camera colonoscope footage—a breakthrough that enhances polyp detection and navigation without requiring expensive labeled data. This contribution has significant clinical implications, as improved depth perception can reduce missed polyps and increase adenoma detection rates, directly impacting patient outcomes. Dr. Hwang's research bridges the gap between computer vision theory and practical medical applications, demonstrating how unsupervised learning can overcome data scarcity in healthcare. His work is particularly notable for addressing the variability of real-world colonoscopy environments, where lighting, tissue deformation, and camera motion pose unique challenges. By advancing autonomous depth estimation for endoscopy, Dr. Hwang is helping pave the way for more reliable, automated colorectal cancer screening tools.
Research Focus
Key Achievements
Top Papers
- 1