Seminar: What Might be Predicted from Medical Image Mining

Seminar: What Might be Predicted from Medical Image Mining

Presenter: 
Dr. Larry Hall
Event Date: 
Thursday, September 24, 2015 - 3:30pm
Event Location: 
138 DeBartolo
Abstract: 
What Might be Predicted from Medical Image Mining Medical imaging provides a noninvasive way of viewing cancerous or precancerous anomalies. The anomalies could be lung nodules or tumors, for instance. They can be brain tumors. The extraction of useful features and building of learned models from CT scans of lungs and magnetic resonance images of brains will be discussed. Experiments will be shown that indicate it is possible to predict disease prognosis or identify a “dangerous” nodule during low dose CT screening. The challenges of using only images for prediction will be discussed, as well as the potential combination of clinical and genetic information to improve predictions from medical images. Lawrence O. Hall is a Distinguished University Professor at the Department of Computer Science and Engineering at University of South Florida. He is currently a Distinguished Fellow of the Notre Dame Institute for Advanced Study and the Melchor visiting Professor in CSE at the University of Notre Dame. He received his Ph.D. in Computer Science from the Florida State University in 1986 and a B.S. in Applied Mathematics from the Florida Institute of Technology in 1980. He is a fellow of the IEEE. He is a fellow of the AAAS and IAPR. He received the Norbert Wiener award in 2012 from the IEEE SMC Society. He is the chair of the IEEE PSPB Publications Conduct Committee and Strategic Planning Committee. His research interests lie in distributed machine learning, extreme data mining, bioinformatics, pattern recognition and integrating AI into image processing. The exploitation of imprecision with the use of fuzzy logic in pattern recognition, AI and learning is a research theme. He has authored or co-authored over 75 publications in journals, as well as many conference papers and book chapters.