Project Segmentation and Analysis of Aortic Aneurysm using Echocardiograms Program DUIRI - Discovery Undergraduate Interdisciplinary Research Internship Term Spring 2025 Status Accepted Research Area AI in Biomedical Image Analysis Description According to the World Health Organization, cardiovascular disease is the leading cause of death worldwide, with over 75% of deaths resulting from cardiovascular disease being in lower- and middle-income countries. One type of cardiovascular disease is the development of aortic aneurysms. Aortic aneurysms result from weakness in the aorta’s wall that leads to wall expansion and ballooning. This expansion can be followed by aortic wall dissection and, finally, rupture, which has a very high mortality rate. The goal of this project is to better predict the progression of ascending thoracic aortic aneurysms (ATAAs), which occur in the portion of the aorta above the diaphragm, using echocardiograms obtained from mice models. We plan on developing and training an artificial intelligence (AI) algorithm for the automated segmentation of the ascending thoracic aortic arch, then adding more parameters to the model like the aortic diameter measurement, etc. that affect the clinical diagnosis and development of an ATAA, based on the American Heart Association (AHA) guidelines. Supervisor Craig J Goergen Mentor Shubh Parag Mehta Type of work required Students assisting with this project would be expected to assist with the understanding of and developing AI algorithms for the classification and segmentation of ATAAs on echocardiograms obtained from mice. Websites https://engineering.purdue.edu/cvirl
https://pubmed.ncbi.nlm.nih.gov/39299353/ Qualifications Students should be interested in medical imaging. Previous coding experience is required, either in MATLAB, Python, or both. A basic understanding of cardiovascular anatomy will be helpful but not required. Credit Hours 0 Weekly Hours 5 (estimated)