Breast cancer is the highest incident cancer in women and a serious threat to a woman's life. Early detection and treatment of breast cancer can reduce the mortality rate. Currently, mammography is widely employed for routine screening of breast cancer. Ultrasound imaging is used as an important adjunct to mammography, especially in the post-screening (diagnostic) phase. Irrespective of the imaging modality, several factors including the level of radiologists' expertise affect the accuracy of breast cancer detection and diagnosis. Computer Aided Detection/Diagnosis (CAD) systems are objective in nature as opposed to the subjective analysis made by radiologists. Many studies show that the use of a CAD system as a second reader has the potential to improve the accuracy of breast cancer detection and diagnosis. Recently, integration of information from multiple sources is gaining wide popularity in data analysis. Information fusion in CAD systems would serve to mimic the radiologist's practice of combining information from multiple mammographic views and from multiple imaging modalities like ultrasound imaging and mammography to arrive at better diagnostic decisions. This study reviews the literature on such CAD systems based on mammograms and ultrasound images for breast cancer detection and diagnosis.
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Dr. Lavanya R. and Nagarajan, N., “Information fusion in CAD systems for breast cancer diagnosisusing mammography and ultrasound imaging: A survey”, Journal of Artificial Intelligence, vol. 7, pp. 113-122, 2014.