Room 515, Cosmology Building, National Taiwan University + Cisco WebEx, Physical+Online Seminar
(實體+線上演講 台灣大學次震宇宙館515研討室+ Cisco WebEx)
Imaging-based Cluster-Informed Lung Assessment and Modeling
Ching-Long Lin (The University of Iowa)
Abstract
In this talk, I will first describe the notion of artificial intelligence and modeling and simulation (AIMS), subject-specific computed tomography (CT) imaging-based computational fluid and particle dynamics (CFPD) lung model, and quantitative CT (qCT) variables and machine learning/clustering. I will then explain the cluster-informed strategy and its multiscale nature. That strategy is applied to three lung disease populations, including asthmatics, chronic obstructive pulmonary disease (COPD) patients and COVID survivors, viz. long COVID or post-acute sequelae of COVID-19 (PASC). The CFPD-predicted particle depositions in asthma and COPD are validated against single-photon emission computed tomography (SPECT) human subject data. Finally, I will present the future plan of developing an integrated post-COVID lung model using chest X-rays as input and its path moving forward toward a digital twin.
Meeting number (access code): 2518 793 4263
Meeting password: 4B3psJErPR4
【Speaker Profile】
Dr. Ching-Long Lin is Edward M. Mielnik and Samuel R. Harding Professor and Departmental Executive Officer of Mechanical Engineering Department at the University of Iowa. Dr. Lin’s research focuses on: (1) developing computed tomography (CT) imaging-based subject-specific lung models, (2) employing machine learning and deep learning of CT lung images to identify imaging clusters and advance a cluster-informed modeling strategy, and (3) conducting CT and single-photon emission computed tomography (SPECT) human subject studies for model validation. Dr. Lin received his B.S. degree from National Taiwan University, and his M.S. and Ph.D. degrees from Stanford University – all in mechanical engineering. He received U.S. NSF CAREER award and is elected Fellow of the American Physical Society (APS), the American Society of Mechanical Engineers (ASME), and the American Institute for Medical and Biological Engineering (AIMBE).
