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Journal of Clinical & Experimental Pathology | ISSN: 2161-0681 | Volume 8
Breast Pathology and Cancer Diagnosis
6
th
World Congress and Expo on
July 25-26, 2018 | Vancouver, Canada
Medicinal Chemistry and Rational Drugs
20
th
International Conference on
&
Colored computer aided diagnosis system for breast mammography
Maha Ali
Sudan University of Science and Technology, Sudan
B
reast Cancer is the most common and life threatening cancer among women. Mammography is a key screening tool for
breast abnormalities detection. It is an effective way that has demonstrated the ability to detect breast cancer at early stages,
because it allows identification of tumor before being palpable. Radiologists may miss the breast abnormality due to the textural
variation of breast tissues intensity in mammogram. So, radiologists may result in false-positive or false-negative results. Efforts
in developing the Computer Aided Detection/Diagnosis (CAD) systems for mammogram analysis improve the diagnostic
accuracy by radiologists. This study developed an algorithm to read mammograms automatically with colors. It proposed
the use of discrete wavelet decomposition technique using Symlet wavelet as a feature extraction, and the linear discriminant
analysis (LDA) as a classifier in order to discriminate the extracted features to find out this detection. The algorithm achieved
98.8% accuracy, 95.0% sensitivity in breast tissue classification. This accuracy has been verified with the ground truth given in
the mini-MIAS database. So, this algorithm will help radiologists for a true diagnosis and decrease the number of the missing
cancerous regions or unnecessary biopsies which are very stressful for women, it can help in early detection of breast cancer,
and following treatment can significantly improve the chance of survival for patients with breast cancer. So, it will save women
lives.
mahaalmona@yahoo.comMaha Ali, J Clin Exp Pathol 2018, Volume 8
DOI: 10.4172/2161-0681-C3-051