Computer aided decision system for early detection of breast cancer.

ABSTRACT

BACKGROUND & OBJECTIVES: Mammography is currently the method of choice for early detection of breast cancer in women. However, the interpretation of mammograms is largely based on radiologist's opinion. In this study an attempt is made to develop an image processing algorithm for the detection of microcalcifications and also a computer based decision system for early detection of breast cancer.The proposed method deals with a novel approach for the development of a computer aided decision (CAD) system for early detection of breast cancer by mammogram image analysis. METHODS: The proposed method employs simple thresholding the region of interest and the use of filters for clear identification of microcalcifications. The method suggested for the detection of microcalcifications from a mammogram image segmentation and analysis was tested over several images taken from mini-MIAS (Mammogram Image Analysis Society, UK) database. The algorithm was implemented using Metlab codes programming and hence can work effectively on a simple personal computer with digital mammogram as stored data for analysis. RESULTS: The algorithm works faster so that any radiologist can take a clear decision about the appearance of microcalcifications by visual inspection of digital mammograms. The performance of the algorithm was tested over several images and the validation of results by visual inspection were done by an expert radiologist. Also, the system has given good detection rate as high as 78 percent. The performance analysis of the CAD algorithm was done by receiver operating characteristics (ROC) plot. INTERPRETATION & CONCLUSION: The CAD system suggested here was capable of detecting microcalcifications with a high detection rate, and thus could be used for early detection of breast cancer.