## 2 Mammogram Image Description and Feature Extraction  
A mammogram is an x-ray exam of the breast. It is used to detect and diagnose breast disease, both in women who have no breast complaints or symptoms and in women who have breast cancer symptoms (such as a lump). The special type of x-ray machine used for the breasts is different than for other parts of the body. This type of machine produces x-rays that do not penetrate tissue as easily as that used for routine chest films or x-rays of the arms or legs, and gives a better image of variations in tissue density. For a mammogram, the breast is squeezed between two plastic plates attached to the mammogram machine unit in order to spread the tissue apart. This squeezing or compression ensures that the calibration will be accurate, that there will be very little movement so the image is sharper, and that the exam can be done with a lower x-ray dose. However, it also makes 3-D reconstruction of the breast structure much more difficult. Mammography produces a black and white image of the breast tissue on a large sheet of film which is interpreted by a radiologist. The appearance of the breast on a mammogram varies a great deal from woman to woman. Some breast cancers produce changes in the mammogram that are difficult to notice. Breast cancer takes years to develop. Early in the disease, most breast cancers have none of the obvious symptoms like lumps. When breast cancer is detected in a localized stage and when it has not spread to the lymph nodes, the five year survival rate is 98% [1]. If the cancer has spread to the auxiliary lymph nodes, the rate drops to 80% [1]. If the cancer has metastasized to distant organs such as the lungs, bone marrow, liver, or brain, the five-year survival rate is only 26% [1]. A screening mammogram is an x-ray exam of the breast in a woman who has no symptoms and usually takes two x-ray images of each breast, as is shown in Figure 1. The goal of a screening mammogram is to find cancer when it is still too small to be felt by a woman or her doctor. Finding small breast cancers early by a screening mammogram greatly improves a woman's chance for successful treatment and survival. Breasts vary in density, which affects the appearance of the breast in mammograms. Examples of the variations are shown in Figure 2. The American College of Radiology (ACR) Breast Imaging Reporting and Data System (BIRADS) characterizes these as ranging from 1-4, with 4 being the most dense. A dense breast presents more non-cancerous structures on a mammogram that can obscure a mass. The majority of work on feature analysis of mammograms has been through CAD efforts, focusing on determining the contextual similarity to cancer and finding abnormalities in a local area of a single image [44, 45]. The primary methods used range from filters to wavelets to learning methods. In this context, filters are equivalent to shapes that are searched for in an image. Wavelets are the result of applying a transform to the image, and learning methods try to apply prior knowledge to combine a set of low-level image features like pixel intensities into an accurate classification. Problems arise in using filter methods [44] because of the range of sizes and morphologies for breast cancer, as well as the difficulty in differentiating cancerous from non-cancerous structures. The size range problem has been addressed by using multi-scale models [45]. Multiple types of filters must be used to handle the variation in the morphology of various cancers. Similar issues affect wavelet methods, although their use has led to reported good results [46] with the size range issue being improved through the use of a wavelet pyramid [47]. Learning techniques have included support vector machines [48] and neural networks [46]. Our analysis starts with CAD prompts to find the contextually similar suspicious points that could be cancers in the mammograms. The CAD technique highlights the areas of the image that have bright cores, a characteristic of spiculated lesions as shown in Figure 3a.