题目：Medical Image Analysis —— Selected Research Projects
时间：2019年11月8日 14:00-15:00
地点：80足球直播吧 F210会议室
邀请人：陈晓军 研究员（生物医学制造与生命质量工程研究所 ）
Biography
Priv.-Doz. Dr. Dr. Jan Egger has over 10 years of experience in developing algor
ithms in medical image analysis and computer vision, including 5 years of postdoctoral research and development in the healthcare industry. He has extensive experience in implementing algorithms and software in the field of surgical planning, and published over 100 peer-reviewed papers and several patents. Dr. Egger holds a PhD and a German Habilitation in Computer Science, and an interdisciplinary PhD in Human Biology. The interdisciplinary PhD was obtained when working in the Neurosurgery Department of the University Hospital in Marburg, Germany, where he developed several algorithms for brain tumors, aneurysms and deep brain stimulation, which can be used within the Operation Microscope, e.g. from BrainLab. His main research interests are Translational Science in Medical Image Analysis and Image-Guided Therapy. Dr. Egger has currently a dual appointment and is employed 50% at the Graz University of Technology and 50% at the Medical University of Graz.
Abstract
In this talk, Dr. Jan Egger will give an overview about several medical applications he has been working on recently with his team. Among other things, he will speak about enFaced, a virtual and augmented reality training and navigation module for 3D-printed facial defect reconstructions. The next project, BioMechAorta, is about mechanics, modeling and simulation of aortic dissection. In more detail, Dr. Egger will speak about the virtual regression of aortic dissections using 3D generative networks. Another project, CAMed, is about clinical additive manufacturing for medical applications, which targets the automatization of cranial implant design for 3D printing with deep learning. Finally, Dr. Egger will talk about Studierfenster (www.studierfenster.at), a recently released client/server based medical cloud platform. Studierfenster offers medical image analysis capabilities for medical data (like CT or MRI) in 2D and 3D directly in a standard web browser.
