Session:

Knowledge Representation, Decision Support and Expert Systems
Tuesday, March 02, 2004, 10.30 – 10.50

Session Chair:
Vice Chair:

A. Dobnikar
M. Savoji

Paper Title:

Image Incorporated Mammogram and Ultrasound Based Expert System For Breast Diseases

Author(s):

U. Kalthum Ngah, Universiti Sains Malaysia, Malaysia
Kim Lin Siew, Universiti Sains Malaysia, Malaysia
Noraini Mat Shariff, Universiti Sains Malaysia, Malaysia
Chan Chee Loon, Universiti Sains Malaysia, Malaysia
Shalihatun Azlin Aziz, Universiti Sains Malaysia, Malaysia

Abstract:

Every woman in the world is at risk for breast cancer. In Malaysia alone, recent statistics show that breast cancer is the number one cause of cancer-related deaths among women. Early detection is most vital for good prognosis and mammography proves to be the best method of detection. Women who are in the high risk group should consider having their first baseline mammograph taken. Most Asian countries have not implemented mass screening as yet. If so, radiologists would be faced with an increased caseload, thereby elevating the chances of improper diagnosis. In practice, both mammography and ultrasound investigations are frequently used to assess breast lesions after undergoing the first assessment i.e. physical examination as the three investigations typically give complementary information. Diagnosticians with the training and experience to interpret mammographic and breast ultrasound images are scarce. An expert system would make diagnostic expertise more widely and readily available in the clinical community. The design and development of an image incorporated mammograph and breast ultrasound expert system has been detailed in this paper. Possible extension to this would be to embed image processing modules on the image based mammograph and breast ultrasound expert system.

Keywords
Expert System, Breast Cancer, Mammogram, Breast Ultrasound