Novel Methods in Medical Image Computing

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CIS Colloquium, Feb 20, 2013, 11:00AM – 12:00PM, Wachman 447

Novel Methods in Medical Image Computing

Allen Tannenbaum , Comprehensive Cancer Center/Electrical and Computer Engineering, University of Alabama

In this talk, we will describe some novel approaches to medical image computing, including segmentation and registration. Segmentation is the process of extracting key features from imagery. We will describe statistical methods for doing this, especially the extraction of various tumor types from a number of modalities including MRI and CT. This will also include new methods for white matter tractography. Very importantly, we will describe some ideas from feedback control that may be used to close the loop around and robustify both open-loop segmentation and registration algorithms in computer vision. In addition to segmentation, the second key component is registration. Registration is the process of establishing a common geometric reference frame between two or more data sets obtained by possibly different imaging modalities. The registration problem (especially in the deformable case) is still one of the great challenges in vision and medical image processing. Registration has a substantial literature devoted to it, with numerous approaches ranging from optical flow to computational fluid dynamics. For this purpose, we propose using ideas from optimal mass transport. We will show how the information gleaned from this may be used to drive certain tumor growth models. We will demonstrate our techniques on a wide variety of data sets from various medical imaging modalities. The talk is designed to be accessible to a broad audience of computer scientists, medical researchers, clinicians, and engineers

Dr.Tannenbaum received his Ph.D. in mathematics from Harvard University. He has held faculty positions at the Weizmann Institute of Science, McGill University, ETH in Zurich, Technion, Ben-Gurion University of the Negev, University of Minnesota, Georgia Tech, and Boston University. He is presently the Goodrich Professor at the Comprehensive Cancer Institute and Department of ECE at UAB where he also serves as Interim Chair. Dr.Tannenbaum has authored or co-authored about 460 research papers, and is the author or co-author of three books: “Invariance and Systems Theory”, “Feedback Control Theory”, and “Robust Control of Infinite Dimensional Systems”. He edited two volumes “Feedback Control, Nonlinear Systems, and Complexity”, and “Mathematical Methods in Computer Vision”. He also has four patents in computer vision and medical imaging. Dr. Tannenbaum has been an Associate Editor of several journals including “SIAM J. Control and Optimization”, “Systems and Control Letters”, “Int. Robust and Nonlinear Control”, “SIAM Journal Imaging Science”. He has won several awards including the Kennedy Research Prize, George Taylor Research Award, IEEE Fellow, SICE Best Paper Award, Foams 2000 Best Paper Award, MICCAI Best Paper Award, and Hugo Schuck Award (Best Paper at ACC). He has given a number of plenary talks including at SIAM, IEEE CDC 2000, MTNS, and SCICADE. He has done research in medical imaging, image processing, computer vision, robust control, systems theory, robotics, semiconductor process control, operator theory, functional analysis, cryptography, algebraic geometry, and invariant theory.