|
3月30 日英国利兹大学Alejandro Frangi教授系列学术报告预告(二)
作者:cwj
发布日期:2019-03-28
浏览次数:
报告时间:3月30日(周六) 14:00-16:00 报告地点:屏峰校区A1区块计算机大楼D301 报告题目:Statistical Shape Modelling in Medical Image
Analysis 报 告 人:Alejandro Frangi 报告摘要: Statistical
shape models are one technology that have revolutionized computer vision and
medical image analysis in the 1990s and 2000s and continues to exert its
influence. SSMs allow computers to learn generative models that can explain the
mean shape and shape variations of an object or organ of interest. This
tutorial will introduce this approach , present the underlying theory and
algorithms, and show extensions and applications for medical image analysis. 报告人简介: Alejandro
Frangi , IEEE Fellow (2014), EAMBES Fellow (2015), Chair of the Fellows
Committee of the IEEE EMBS (2017). He is a Diamond Jubilee Chair in
Computational Medicine at the University of Leeds, and the director of the
Center for Computational Imaging and Simulation Technologies in Biomedicine of
University of Leeds. Prof. Frangi has main research interests at the crossroad
of medical image analysis and modeling with emphasis on machine learning
(phenomenological models) and computational physiology (mechanistic models). He
has particular interest in statistical methods applied to population imaging
and in silico clinical trials. His highly interdisciplinary work has been
translated to the areas of cardiovascular, musculoskeletal and neuro sciences. Prof
Frangi been principal investigator or scientific coordinator of over 25
national and European projects, both funded by public and private bodies. He
has edited several books, published 7 editorial articles and over 200 journal
papers in key international journals of his research field and international
conference papers with an h-index 53 and over 19,400 citations according to
Google Scholar. He has been three times Guest Editor of special issues of IEEE
Trans Med Imaging, one on IEEE Trans Biomed Eng, and one of Medical Image
Analysis journal. Prof Frangi is Chair of the Editorial Board of the
MICCAI-Elsevier Book Series (2017-2020), and serves as Associate Editor of IEEE
Trans on Medical Imaging, Medical Image Analysis, SIAM Journal Imaging
Sciences, Computer Vision and Image Understanding journals. |