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Breast cancer has been reported by American Cancer Society as the second leading cause of death among all the cancers of women. It is also reported that the early detection of breast cancer can improve survival rate by allowing a wider range of treatment options. Mammography is believed to be an effective tool to help radiologists to detect the malignant breast cancer at the early stage. It is the most effective technique for breast cancer screening and can be used for the early detection of masses or abnormalities. Small clusters of micro calcifications appearing as collection of white spots on mammograms show an early warning of breast cancer. In digital mammography, electronic image of the breast is taken and is stored directly in a computer. Image enhancement techniques can improve the quality of mammogram images with enhancing the details of key features, like the shape of microcalcifications. This thesis proposes a new enhancement algorithm based on combination of different processing techniques.
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Mammography is one of the best known methods in breast cancer detection, but in some cases, radiologists cannot detect tumors despite their experience, mainly because of the noise present in mammogram images and also low contrast present in them. To aid the radiologists mammogram images need to be enhanced so that diagnosis results are accurate.
