Invited Talk: Essam Rashed – Human head models with deep learning enabled dielectric properties, Feb 25th 2021, 8:15 AM CET

Dr. Essam Rashed has been working in many fields of medical image processing. Therefore, it’s a great pleasure to host him as a virtual guest in our lab!

Title: Human head models with deep learning enabled dielectric properties
Date: Feb 25th 2021, 8:15 AM CET

Abstract: Transcranial magnetic stimulation (TMS) is a commonly used clinical procedure for neurophysiological characterization. Personalized TMS requires a pipeline for individual head model generation to provide target-specific brain stimulation. This process includes intensive segmentation of several head tissues based on MRI data, which has significant potential for segmentation error, especially for low-contrast tissues. Uniform electrical dielectric properties are assigned to each tissue in the model, which is an unrealistic assumption based on conventional volume conductor modeling. In this talk, I will briefly highlight this problem and discuss new approaches for fast and automatic estimation of the dielectric properties in the human head models without anatomical segmentation.

Short Bio:Essam Rashed received his B.Sc. in Scientific Computing in 1998 and M.Sc. in Computer Science in 2002, both from Suez Canal University, Ismailia, Egypt. He received Ph.D. (Eng.) in Computer Science from the University of Tsukuba, Tsukuba, Japan in 2010. From 2010 to 2012, he was a Research Fellow of the Japan Society for the Promotion of Science (JSPS) at the University of Tsukuba, Japan. He served as Assistant Professor of Computer Science at the Department of Mathematics, Faculty of Science, Suez Canal University from 2012 to 2016. Since then, he was promoted to Associate Professor at Suez Canal University, Egypt and worked at Faculty of Informatics and Computer Science, The British University in Egypt on Secondment. Currently, he is a Research Associate Professor at Nagoya Institute of Technology. His research interests include medical image processing, data analysis and visualization, deep learning and pattern recognition. Dr. Rashed is  IEEE Senior Member and Associate Editor of IEEE Access. He is a recipient of the Egyptian National Doctoral Scholarship (2006), JSPS postdoctoral fellowship (2010), JAMIT best presentation award (2008 \& 2012), and Chairman Award, Department of Computer Science, University of Tsukuba (2010). He participated as a PI and CoI for several external funded projects.