# Breast Microcalcification Detection Algorithm Based on Contourlet and ASVM
## 1 Introduction  
Breast cancer is a common malignant tumor with high morbidity and mortality. It has become one of the main threats of women's health and life. According to data provided by the American Cancer Society (ACS) in 2019, there are 1,762,450 new cancer cases in the United States and 606,880 deaths caused by cancer. The United States will have 271,270 women with breast cancer that year, and 42,260 expected cases of breast cancer deaths [1]. Moreover, 274,000 new cases of breast cancer with 66,000 deaths are expected to be annually diagnosed in China. It is found that the breast cancer is the fastest growing rate of cancer in China [2].  
The exact cause of breast cancer is unclear and there is no effective way to prevent breast cancer. However, a large number of studies have shown that breast cancer screening is an effective way to improve the early detection and cure rates of breast cancer. Common methods for breast cancer diagnosis include the clinical breast examination, imaging diagnosis, and histopathological biopsy. Moreover, commonly used examination methods for breast include mammography, ultrasound, magnetic resonance imaging, and the computed tomography [3]. Due to mammography non-invasiveness,reproducibility and comprehensive sampling, it has occupied a privileged position in the diagnosis of breast diseases. It is relatively inexpensive and yields a clear image. Moreover, mammography can show early lesions that are not easily detectable by visual inspection. It is highly sensitive to the intramammary calcification, especially small the calcification. Common X-ray findings of breast cancer include mass, microcalcification, changes in the nipple and areola, structural distortion, and increased vascular deformation [4]. Among them, the mass and microcalcification are the most important and obvious pathological signs of breast cancer, which are of great significance from cancer detection and diagnosis point of view.  
Microcalcification may occur in both benign and malignant breast lesions. Especially for the early \"occult\" breast cancer, microcalcification is usually the only sign [5]. Meanwhile, mammography is more sensitive to microcalcification.  
With the development of computer-based technologies, the computer-aided diagnosis has been introduced into the medical field and, has enabled doctors to make more accurate clinical diagnoses. Computer diagnostics can save doctors' diagnostic time and increase the accuracy of diagnostic results. Statistics show that with the advent of computer-aided diagnosis systems, the detection rate of breast cancer increased by 20% [6]. Between anatomic pathology and imaging diagnosis, [PERSON] [7] offers a significant new way to improve the analysis of microcalcification for breast cancer. [PERSON] [8] aimed of this study was to explore the relationship between the imaging parameters most commonly used for the study of mammary microcalcification and the corresponding histological and chemical properties. [PERSON] [9] study that breast sample biopsies with microcalcification underwent energy dispersive X-ray microanalysis to better define the elemental composition of the microcalcification. [PERSON] [10] uses digital pathology to lay the foundation for teamwork between anatomical pathology and nuclear medicine. [PERSON] [11] selected from patients who had been examined using breast mammography. The control group did not have detectable microcalcification and was matched in a ratio of 1:3. The clinic-pathological factors, progression-free survival, and overall survival were evaluated by SPSS.