ECE 507 Seminar (Fall 2015)

ECE 507 Seminar (Fall 2015)
2.00–3.15pm Friday, November 6th, Room EB-103
Biomedical Image Computing:
Where computation, imaging and medicine come
Xubo Song,
Center for Spoken Language and Understanding,
Dept of Medical Informatics and Clinical Epidemiology,
Oregon Health and Science University, Portland, Oregon.
Biomedical image computing is an interdisciplinary approach to develop
computational algorithms and technologies for the analysis and visualization of
medical image data. The computation can occur at a range of scales, across a range
of image modalities, and can go from individual patients to large populations. Such
computation can provide tools to help address biomedical problems, for disease
detection, diagnosis and treatment intervention, and for inferring the structure and
function of complex biological systems.
In this talk, I will talk about the projects on biomedical imaging computing that are
carried out in my lab. I will start with an overview of biomedical imaging computing,
and then provide details of some individual projects, from cardiac motion tracking,
to breast cancer image analysis, to accelerometer-based human movement
tracking. I will discuss the algorithmic components for these projects, specifically
on image registration, segmentation and tracking. I will conclude with a brief
overview of other biomedical signal processing projects at the CSEE program at
Xubo Song received the BS degree from Tsinghua University in 1992, and the MS
and PhD degrees in electrical engineering from the California Institute of
Technology in 1994 and 1999, respectively. She joined the Oregon Graduate
Institute of Science and Technology (which later merged with Oregon Health and
Science University) in 1998 as an assistant professor in the Department of Electrical
and Computer Engineering. Currently, she is a Professor at the Center for Spoken
Language and Understanding (CSLU) and the Department of Medical Informatics
and Clinical Epidemiology (DMICE) at OHSU. Her research interests include machine
learning, image processing and analysis, and medical imaging.
All welcome