Quality Enhancement Techniques for Breast Carcinoma in Epithelial Tissue Identification Process

Abstract

Breast Cancer is considered to be the deadliest disease among women due to the carcinoma in epithelial tissue development in breast. The cause of the disease many vary due to many circumstances, but identification procedure followed are mostly similar. The clinical way of identifying the cancer effected tissues in breast are followed in advance stages or pre advanced stages, which is due to the lack of adequate knowledge about breast cancer. The treatment given during the final stages are mostly not feasible solution and eventually ends with negative result. Digital Image Processing (DIP) technique coupled with Data Mining and Machine learning algorithms are most recently used breast cancer identification procedure. The identification procedure followed using those techniques are not only accurate, it also gives very fast analyzing report based on the historical record. This research article proposes pre-processing technique, which is a part of the overall research work of breast cancer identification procedure. The Mammography images collected from the source may contains many irrelevant information as well as missing values. The article gives a clear idea of pre-processing techniques followed as well as filtering techniques implemented to enhance the quality of the collected breast cancer Mammography images.