Medical image analysis and software
My research area is in medical image analysis, broadly defined as the extraction of quantitative information from medical images. I am particularly interested in problems where the development of innovative algorithm strategies has a direct coupling to treatment delivery in "real-time" an example of this is my work in the development of research interfaces for image-guided neurosurgery, which enabled the bridging of cutting-edge image analysis methodology to the operating room environment in a way that enables its evaluation without changes to the actual surgery and also the design of our real-time fMRI biofeedback system which uses real-time motion compensation to allow the use of fMRI as a potential treatment modality. I have also been actively involved in developing both methods and software for fMRI connectivity analysis, some of which can be found in our Yale BioImage Suite software package, whose development I originated and still coordinate. I teach a class titled "Medical Software Design," which formed the basis for the textbook "Introduction to Medical Software: Foundations for Digital Health, Devices, and Diagnostics" (Cambridge University Press 2022) and the companion Coursera Class "Introduction to Medical Software" (Yale/Coursera 2021).
Xenios Papademetris received his BA from Cambridge in 1994 in Electrical Engineering and Information Sciences with First Class Honours and his PhD in 2000 in Electrical Engineering at Yale, where he was awarded the Harding Bliss Prize for Excellence in Engineering and Applied Science. He has been on the Yale faculty since 2003 and is currently a professor of Radiology, and Biomedical Imaging and Biomedical Engineering.
From medical image computing to computer-aided intervention: development of a research interface for image-guided navigation(2009)
Segmenting the Brain Surface From CT Images With Artifacts Using Locally Oriented Appearance and Dictionary Learning(2019)
Cambridge University Press (2021)