Graduate Student in Computer Science, Gachon University, South Korea
📧 xenotic [at] gachon.ac.kr | Google Scholar

Medical Image Analysis · Volume Visualization

Developing advanced techniques for image-based diagnostics and decision support.
Techniques:

• ROI detection & segmentation in medical scans (CT/MRI)
• Patient-to-image registration pipelines (deep learning, RGB-D data, SVD & ICP)
• Computer-aided diagnosis system (CDSS) design

Crafting interactive visualization frameworks for volumetric medical data to aid clinical workflows.
Techniques: Direct Volume Rendering, semi-automated Transfer Function design using visual saliency, GPU optimization.

Maintaining reproducibility and collaborative efficiency in research.
Tools: PyTorch, Git, Docker, LaTeX

• X-ray–based CT Reconstruction: Deep learning models for reconstructing volumetric CT from limited X-ray views.
• Gaussian Splatting for Medical Imaging: Applying 3D Gaussian Splatting to enhance quantitative analysis and visualization.
• Neural Rendering: Exploring neural rendering frameworks for accurate and efficient medical image reconstruction.