Feature Extraction and Enhancement Of Breast Cancer Mammogram Noisy Image Using Image Processing


In recent days, breast cancer [1] is gradually becoming a significant cause of death in female cancer patients in developing countries. Approximately 2.1 million women are dying globally due to this fatal endemic. The diversified image processing techniques are applied in malignancy research to extract the pragmatic attributes from mammographic images for effective decision making or diagnosis. Mammograms are the X-rays scanning of the breast used by the oncologist to visualize the early appearance of cancer with the aid of various images processing techniques. Oncologists investigate the micro-calcifications using image processing approaches that detect white specks (microscopic calcium substance) on the mammogram(s). The lumps on breast do not cause cancer, but if it appears in a cluster or certain pattern may lead as early stages of cancer. The aim of our research is to enhance the image and detect the carcinogenic cells by using different existing image filtering approaches with a comparative analysis of their output performance(s). The detection analysis helps in predictions [2] of breast cancer at the beginning stage, which can save many precious lives.



Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL