Breast cancer is the leading cause of cancer death. India has witnessed 30% of the cases of breast cancer during the last few years and it is likely to increase. Breast cancer in India accounts that one woman is diagnosed every two minutes and every nine minutes, one woman dies. The chances of correct treatment and survival are greatly increased by early diagnostics, but this process is tedious and often leads to a disagreement between pathologists. Early detection and diagnosis can save the lives of cancer patients. Issues such as technical reasons, which are related to imaging quality and human error have increased the misdiagnosis of breast cancer in radiologists’ interpretation. In the effort to overcome such restrictions, CAD systems are developed to automated breast cancer detections and classify benign and malignant lesions. Computer-aided diagnosis systems have the potential to improve diagnostic accuracy. By A Computer Aided Diagnosis system, Breast cancer can be detected as early as possible. By Early prevention the chances of death can be reduced . Our Project presents a method to detect breast cancer by employing techniques of Machine Learning. The carried out an experimental analysis on a dataset to evaluate the performance. The proposed method has produced highly accurate and efficient results when compared to the existing methods. This Project utilizes the CNN algorithms for the High Accuracy in the results and the prediction of cancer Affected percentage .Overall , this project seek to the early detection of breast cancer by Hypothetical images with high accuracy using CNN and overcome the drawbacks in the existing Systems.

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