Cardiovascular Modeling and Simulations to Improve Treatment of Heart Diseases
Cardiovascular diseases are one of the leading causes of death worldwide. We will discuss our group’s recent efforts in using advanced medical imaging and machine-learning based finite-element modeling to better diagnose and treat various cardiovascular diseases. We will first present our group’s recent developments in physics-informed machine-learning that can be used to regularize sparse observational data by embedding know physical laws into the loss functions. We will demonstrate the performance of this framework in patient-specific vascular geometries (e.g., aorta, idealized arteries) and subsequently validation in real-world imaging data. We will also discuss our group's work in advanced medical imaging, and in particularly, CT myocardial perfusion imaging to better detect diseased heart vessels, specifically those that limit blood flow to the heart muscles. Lastly, we will discuss recent directions within our group to characterize durability of tissue-mimicking materials towards advancing and improving bioprosthetic heart valves.
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Owais of Toronto Metropolitan University
Cardiovascular Modeling and Simulations to Improve Treatment of Heart Diseases
Cardiovascular diseases are one of the leading causes of death worldwide. We will discuss our group’s recent efforts in using advanced medical imaging and machine-learning based finite-element modeling to better diagnose and treat various cardiovascular diseases. We will first present our group’s recent developments in physics-informed machine-learning that can be used to regularize sparse observational data by embedding know physical laws into the loss functions. We will demonstrate the performance of this framework in patient-specific vascular geometries (e.g., aorta, idealized arteries) and subsequently validation in real-world imaging data. We will also discuss our group's work in advanced medical imaging, and in particularly, CT myocardial perfusion imaging to better detect diseased heart vessels, specifically those that limit blood flow to the heart muscles. Lastly, we will discuss recent directions within our group to characterize durability of tissue-mimicking materials towards advancing and improving bioprosthetic heart valves.
Biography:
Dr. Owais Khan is an assistant professor in the Department of Electrical, Computer and Biomedical Engineering at the Toronto Metropolitan University. His lab combines computational simulations, advanced medical imaging and biomechanics to tackle challenging problems in cardiovascular medicine. Through a multi-disciplinary approach, his group is developing novel biomarkers of vascular diseases, and designing personalized and patient-centric treatment strategies to improve outcomes of vascular diseases. Dr. Khan received his BASc, MASc and PhD in mechanical engineering from the University of Toronto, the latter in joint affiliation with the University of Oslo (Norway). He completed his postdoctoral training at Stanford University funded by NSERC Postdoctoral Fellowship (2017) and American Heart Association Postdoctoral Award (2019).
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Address:245 Church St. , , Toronto, Ontario, Canada, M5B 2R2