GRAND seminar
12:00 noon, Dec 06, Thursday, 2007, by Ajay Nagarajan
ST2, 430A

Machine learning techniques in image analysis of Bio-Structures

Abstract

Biological problems are motivating innovations in computational sciences. In particular, biomedical image analysis is done to extract information from biomedical images for diagnosis, further research and development. Generally bio-images are analyzed based on their textural and geometric characteristics. There are a number of cases in biomedical informatics where the primary data source would be chunks of biomedical images. In such cases, machine learning techniques could be advocated in Bio-medical image analysis for a various number of reasons, most important of which would be to develop and maintain a knowledge based system. The aim of this talk is to throw light on machine learning techniques that are already employed / could be potentially employed in image analysis of bio-structures. The talk will also cover real time applications of modern incremental machine learning techniques like Ripple-Down-Rules.

Biography

Ajay Nagarajan received his Bachelor of Engineering (B.E.) in Computer Science and Engineering from Anna University, Chennai, India in 2007. He is now pursuing his integrated PhD in Computer Science at George Mason University. His research interests include Human-Computer Interaction, Computer Graphics, Biomedical Informatics and Machine Learning.




Department of Computer Science
Volgenau School of Information Technology and Engineering
George Mason University