Title: A colored CAD system for breast mammography

Biography:

Maha A Elhady Almona Ali has her exper se and passion in improving the mammograms reading. Her algorithm creates new pathways for improving women healthcare and save their lives. She has developed this algorithm a er years of experience in research, applied her algorithms on mammograms from sites for scien fi c researches and mammograms from hospitals. The algorithm is based on wavelet decomposi on technique which is a powerful tool for image analysis.
 

Abstract

Breast Cancer is the most common and life threatening cancer among women. Mammography is the process of using lowenergy X-rays to examine the human breast. It is one of the best examina on procedures for early detec on of breast cancer. Mammograms are the most diffi  cult of radiological images to interpret since they are of low contrast. Radiologists typically diagnose breast abnormali es and indicate their regions from mammograms. Some mes due to small masses or breast density radiologists may miss the suspicious regions, so the diagnosis can fail. Therefore, eff orts in developing Computer Aided Detec on/Diagnosis (CAD) algorithms for mammogram analysis will assist radiologist in images interpreta on for accurate diagnosis and effi  cient detec on of cancer cells in the earlier stages. This study developed an algorithm to analyze mammograms automa cally with colors, in order to detect the abnormal breast  ssue. It proposed the use of the Discrete Wavelet Decomposi on (DWD) technique using symlet wavelet to fi nd out this detec on. Diff erent sets of proposed combina on techniques based on the DWD technique were used in order to obtain the best accuracy in breast  ssues classifi ca on. The study showed that the combina on between the un-decimated DWD technique and the Spa al Gray Level Dependency Matrix (SGLDM) achieved
the best result. It achieved 98.8% accuracy, 95.0% sensi vity. This accuracy has been verifi ed with the ground truth given in the mini-MIAS database. This algorithm will help to spare women unnecessary and stressful biopsies.