Evaluation of SUSAN Filter for the Identification of Micro Calcification

Nowadays breast cancer is one of the major causes of death among women. This shows an early diagnostic techniques is critical for women’s quality of life. Mammography is the main test used for screening and early diagnosis of breast cancer. Since micro calcifications are space-occupying lesions, described by their shapes, margins etc several image processing based techniques have been developed to improve the detection of primary signatures of this disease to increase radiologist’s diagnostic performance. This paper presents an image processing based technique used for cancerous tumor mass segmentation. The processing techniques include enhancing the quality of the image, reducing the noise using filtering technique, segmenting the cancerous regions using SUSAN edge detection algorithm. The method was tested on 375 mammography images and achieved a sensitivity of 89%. General Terms Pattern Recognition, Image Processing, Computer Vision.