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11月8日英国谢菲尔德大学Alejandro Frangi教授学术报告预告
作者：cwj
发布日期：2017-11-06
浏览次数：
报告题目：Cardiovascular and musculoskeletal computational imaging and modelling
报 告 人：Alejandro Frangi教授 (英国谢菲尔德大学）
报告时间：11月8日(周三) 13:30-15:10
报告地点：屏峰校区A1区块计算机大楼D313
报告摘要：
In this talk, Prof. Frangi will provide an overview on research they are carrying out at the Centre for Computational Imaging & Simulation Technologies in Biomedicine (CISTIB) in musculoskeletal and cardiovascular image analysis. Their research emphasis lies in developing advanced methods at the interface between imaging and modelling. They develop new image-based modelling and new model-based imaging and image analysis methods. In addition, they are also interested in addressing the challenge of large-scale image analytics to extract imaging biomarkers from population imaging resources like the UK Biobank or contribute to in silico clinical trials of medical devices in virtual populations of patient-specific models. The talk will provide both an overview of our vision and some of the specific projects and steps we are taking in this arena.
报告人介绍：
Alejandro (Alex) Frangi is Professor of Biomedical Image Computing at theUniversity of Sheffield(USFD) and affiliated to the Electronic & ElectricalEngineering Department. He is also Director of the Center for Computational Imaging and Simulation Technologies in Biomedicine and member of INSIGNEO Institute for in silico Medicine. Prof Frangi is Fellow of IEEE.The INSIGNEO Institute for in silico Medicine is an initiative between the Faculty of Engineering and the Faculty of Medicine at the University of Sheffield and the Sheffield Teaching Hospitals Foundation Trust. INSIGNEO will realise the scientific ambition behind the Virtual Physiological Human (VPH), producing a transformational impact on healthcare. INSIGNEO performs cutting edge research in areas of fundamental and applied biomedical modelling, imaging and informatics. It will pursue the research agenda of the VPH initiative; in particular, in the first five years it will focus on the Digital Patient, In Silico Clinical Trials, and Personal Health Forecasting. It will achieve transformational impact on healthcare through multidisciplinary collaboration in strategic areas, which initially will include personalised treatments and independent, active and healthy ageing.
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