Junho Lee

Hello! I’m Junho Lee, an undergraduate student in the Department of Computer & Artificial Intelligence at Jeonbuk National University (JBNU).
I am currently conducting research at MacsLAB (Medical AI Laboratory), focusing on medical image analysis and deep learning model development.
My main interests include improving AI model accuracy, automating medical data preprocessing, and developing web-based medical image viewers.

I primarily work with PyTorch for modeling and FastAPI + Vue3 (TypeScript) for full-stack development.
To make AI models deployable in real clinical environments,
I design and implement the entire pipeline—from backend to frontend to AI model integration—myself.

Balancing research and development, I aim not only to enhance performance but also to design practically usable systems.
In particular, I focus on improving DICOM viewer UX/UI, AI result visualization, and interactive measurement tools,
developing interfaces that can be applied directly in medical practice.

🔬 Main Research & Projects

• DICOM Viewer Development: Displays medical images (CT, X-ray, etc.) with distance, angle, and area measurement tools and window-level adjustment functions
• AFF (Atypical Femoral Fracture) Detection Model: Built PyTorch-based CNN model and Grad-CAM visualization pipeline
• Medical Image Analysis Web Platform: Integrated FastAPI backend and Vue3 frontend, deployed on the cloud
• MNIST Classification Model: Trained MLP model for handwritten digit (0–9) recognition and developed a visualization dashboard
• Automatic DICOM Metadata Parsing & Pixel Scaling: Implemented precise measurements using actual physical units (mm/px)

🧭 Future Goals

• Enhance explainability of AI models through visualization research
• Commercialize and optimize web-based diagnostic assistance systems for medical imaging
• Build a general-purpose medical imaging platform applicable to various medical datasets

💡 References & Links

• View Projects
• GitHub · LinkedIn

🗺️ Research Topic Mindmap

- Medical AI Projects
  - DICOM Viewer
    - Measurement Tool
    - Window Level / UI Optimization
  - AFF Detection
    - PyTorch CNN
    - Grad-CAM Visualization
  - Web Platform
    - FastAPI Backend
    - Vue3 Frontend
  - Future Work
    - Explainable AI
    - Clinical Deployment