기계 공학부 구성원들의 많은 관심과 참여 부탁 드립니다.

▣ 주   제: 심장혈관계 질환의 진단과 치료 결과 예측을 위한 해석 방법 개발과 적용

▣ 연   사: 김현진 교수

▣ 소   속: KAIST 기계공학과

▣ 일   시: 2022. 2. 4.(금) 10:00

▣ 장   소: 제4공학관 D404호

▣ 초   청: 이준상 교수

▣ 초   록

Computational models of the cardiovascular system have evolved considerably over the last several decades. Numerous approaches based on computational mechanics, multi-physics modeling, solution of inverse problems, optimization, uncertainty quantification, machine learning, and others have been developed and applied in the context of medical image based, patient-specific models to better understand the physiology and pathophysiology of the cardiovascular system, to diagnose the severity of cardiovascular disease, to predict the outcome of a surgery or an intervention, and to virtually test the efficacy and the risk of medical devices. These tools have been proven effective for many of such applications and have promoted an increasing transition of numerical models from research to clinical tools. In many cases, medical device companies and startups have transformed these technologies into validated, clinically approved technologies. Recent advances in this field also include the phenomenal increase in approaches based on machine learning, medical image processing and the development of cardiovascular digital twins.

I will introduce various computational methods and applications that have been conducted to better understand blood flow and pressure in the cardiovascular system. The methods include:

· The coupled multidomain method and applications

· The coupled momentum method and applications

· Autoregulatory mechanism development and applications

· Simulated perfusion framework development and applications

· Solver stabilization strategy

· Mesh adaptation

· Physics-based reduced order solver development and applications