Seminar

Engineering HDR Seminar Series 16, 2013: A Computer-aided Detection System for the Evaluation of Breast Cancer by Mammographic Appearance and Lesion Size

Ms Sheeba Jenifer Sujit , Mechatronics postgraduate student


Date: 2013-03-29
Time: 11:00 to 12:00
Venue: Engineering Meeting Room 2, 5-4-03


Abstract

Breast Cancer has been the leading cause of death among women in the world. Mammography is one of the proven reliable methods for early detection of breast cancer. Although it reduces the mortality rates by 25-30%, the interpretation of digital mammograms is still found to be a very difficult task. It requires skill and experience from trained radiologists. Having a good tool to help the radiologist in the difficult task of mammographic interpretation would be an advantage for early detection of breast cancer. The purpose of this research is to develop a computer aided detection (CAD) tool with more accuracy and improved sensitivity and specificity. Segmentation algorithms are developed to seperate the region of interest. Features that are extracted from digital mammograms are fed to Artificial Neural Networks. Artificial Neural Networks are trained to detect and classify the mammograms in to two types: benign and malignant.  This helps  the radiologist in the difficult task of mammographic interpretation and   early detection of breast cancer.

About the Speaker

Sheeba Jenifer Sujit received her BEng in Electrical and Electronics Engineering  in 1999 and MEngg in Electronics and Communication Engineering (Applied Electronics)  in 2000 from Bharathiar University (India) . Since then she has been actively involved in teaching and research in various universities in India and Malaysia. She started her PhD studies in Monash University from March 2012 under the supervision of Dr.S.Parasuraman. Her research topic is “A Computer-aided Detection System for the Evaluation of Breast Cancer by Mammographic Appearance and Lesion Size”.