Noninvasive Low Cardiac Output Detection via Thermographic
Justin Baba, Ph.D.
Brief Description of Project:
Development of AI based image quality classification, segmentation, characterization tools to facilitate the development of a quantitative metric for temperature based assessments of cardiovascular system operation using noninvasive visible and infrared camera images for Low Cardiac Output Syndrome prediction in neonates post open heart surgical repair of congenital heart disease defects.
Image processing, AI based algorithm development experience
Nature of Supervision:
Vanderbilt Biophotonics center graduate student and PI mentorship and supervision
A Brief Research Plan (period is for 10 weeks):
Week 1: Research Orientation and training
Week 2-3: Background research on the project via literature review
Week 4-5: Imaging data collection and analysis process familiarization
Week 6-9: AI algorithm/tools development and implementation
Week 10: Results analysis and project report and summary and final presentation
Number of Open Slots: 1
Name: Justin Baba
Department: Biomedical Engineering