Department of Computer Engineering
S E M I N A R
Sequence Based Classification for Automated Diagnosis and Grading of Cancer
Computer Engineering Department
Automated diagnosis systems are important medical applications of machine learning, computer vision and pattern recognition which aid to doctors to make decisions. Many researches are made in this area. However, it is difficult to implement a system which is suitable for the different image variations. In order to deal with this problem, images are labeled according to image graphs. Then label information of the images is used by simple graph algorithms to create a sequence. Finally, images are classified. Since classification performances depend on the sequences, our research study focuses on finding most suitable sequences for cancer images.
Keywords: automated diagnosis, sequence generation
DATE: 30 April, 2012, Monday @ 17:00