Medical Image & Video Processing
Automated analysis of leukocytes and nailfold blood flow.Overview
This project explores AI-powered medical imaging for hematology and microvascular screening. By counting white blood cells (WBCs) and analyzing nailfold capillary flow, clinicians gain early warnings about infections or systemic diseases without invasive procedures.
Components
- Classical and deep vision models for WBC segmentation and counting
- Nailfold video analytics that track blood flow velocity and vessel morphology
- Reporting tools that summarize abnormalities for clinicians and researchers
Description
White Blood Cells (WBCs), also called leukocytes, are an important part of the immunes system. Hidden infections and undiagnosed medical conditions could be estimated by counting the WBCs. Nailfold capillary is micro-vessel placed under nail. Our research is to build non invasive WBC system by analyze the blood flow within nailfold capillary using machine learning.
Yuli Sun Hariyani
Assistant Professor, Telkom University
Her research interests include image processing and biomedical image processing.
Suwhan Baek
Researcher, Posco Holdings
His research interests include Medical AI, Auto ML, reinforcement learning, generative models, and SNN.
Cheolsoo Park
Professor
His research interests include machine learning, adaptive signal processing, computational neuroscience, and wearable technology.