Breast cancer is the second leading cause of cancer death after lung cancer among women. The greatest effect on reducing mortality in breast cancer comes from the detection and treatment of invasive cancer when it is as small as possible. Accurate preoperative diagnosis of breast lesion is essential for optimal treatment planning. In order to avoid unnecessary patient distress, it is important to achieve the definite diagnosis without delay and with as few biopsies as possible. Nowadays, when breast cancer is one of the most frequently diagnosed malignancies among women, cost-effective ways for its diagnosis are necessary. Various methods are being performed on mammographic images to detect it at the early stage. This paper describes the Analysis of the breast MR images with the help of wavelet transform. The first step is to apply histogram modification technique to improve the contrast of the image. Then de-noising and filtering are used to remove unwanted data. Finally DWT is used to separate the frequencies and IDWT and thresholding is used for the final detection of cancer.

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Breast MRI Breast cancer detection Wavelet Transform