Involuntary diagnosis of intraductal breast images using gaussian mixture model

Abstract

Intraductal Carcinoma is a noninvasive condition in which abnormal cells are found in the lining of a breast duct. The abnormal cells have not spread outside the duct to other tissues in the breast. During some cases, Intraductal Carcinoma may become persistent cancer. Also spread to other tissues, though it is not known at this time how to predict which lesions will become invasive. Intraductal cancer is the most common type of breast cancer in women. Memory Intraductal includes 3-types of cancer: Usual Ductal Hyperplasia (UDH), Atypical Ductal Hyperplasia (ADH), and Ductal Carcinoma in Situ (DCIS). So the system of detecting the breast microscopic tissue of UDH, ADH, DCIS is proposed. The current standard of care is to perform percutaneous needle biopsies for diagnosis of palpable and image-detected breast abnormalities. UDH is considered benign and patients diagnosed UDH undergo routine follow-up, whereas ADH and DCIS are considered actionable and patients diagnosed with these two subtypes get additional surgical procedures. The systems classify the tissue based on the quantitative feature derived from the images. The statistical features are obtained. The approach makes use of preprocessing, Cell region segmentation, Individual cell segmentation, Feature extraction technique for the detection of cancer.