David Paylan
Pronouns: He/him/his
Research Mentor(s): Kayvan Najarian, Professor
Research Mentor School/College/Department: Department of Computational Medicine & Bioinformatics, Michigan Medicine
Presentation Date: Thursday, April 22, 2021
Session: Session 1 (10am-10:50am)
Breakout Room: Room 15
Presenter: 6
Abstract
While doctors use their eyes to understand and interpret coronary artery data provided by Magnetic Resonance Angiography (MRA) or Computed Tomography Angiography (CTA), researchers have been looking for ways to use technology to automatically track coronary arteries. This document looks to combine two methods of interpreting angiograms, Kalman filtering and a geometric vessel model in order to glean a fuller estimate of a coronary artery’s radius. So far, I have created an algorithm in MATLAB to detect radii across different artery connections. The next step is to compare these radii results to formulae referenced in other research papers and apply the two aforementioned methods to improve the accuracy of my radii measurements. A better estimate of a coronary artery’s radius will prove vital to doctors, who, in relying on their eyes to interpret coronary artery data, might struggle to differentiate noise from weak stenosis requiring treatment. Further, these doctors, though they differ from each other on how they treat varying levels of stenosis, would love to have a standardized way of understanding how severe the stenosis is, and having a more reliable radius will provide exactly that.
Authors: David Paylan, Lu Wang, Kayvan Najarian
Research Method: Computer Programming
