Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorLim, Wei Keaten_US
dc.description92 p.en_US
dc.description.abstractBreast cancer is the most common cancer affecting Singapore women. Every year, 700 - 1000 new cases of breast cancer are diagnosed and about 250 women die from the disease. High-quality mammography, an X-ray technique that vi-sualizes the internal structure of the breast, is the most effective early detection technology currently available. It is sensitive to screening and diagnosis. Un-fortunately, it results in a high false-positive rate, i.e. only a small portion of masses found on mammograms are malignant. Recent studies found that only 20-30% mammographically suspicious nonpalpable breast masses were malig-nant. The National Cancer Institute of America also reported that 80% of American women who undergo surgical breast biopsies do not have cancers. Considering the cost of biopsy and the patient's emotional disturbance, it is crucial to develop high-performance computer-aided diagnosis (CAD) systems to assist radiologists in the classification of breast cancers in order to reduce unnecessary biopsies.en_US
dc.rightsNanyang Technological Universityen_US
dc.subjectDRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligenceen_US
dc.titleDevelopment of an intelligent system for breast cancer diagnosisen_US
dc.contributor.supervisorEr Meng Jooen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Engineeringen_US
item.fulltextWith Fulltext-
Appears in Collections:EEE Theses
Files in This Item:
File Description SizeFormat 
  Restricted Access
9.36 MBAdobe PDFView/Open

Page view(s)

Updated on Jan 26, 2021


Updated on Jan 26, 2021

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.