Detection of Breast cancer with Hybrid image segmentation and Otsu's thresholding

Now a days, the Breast cancer becomes very dangerous for women's life survival. In this paper, the processed mammography images are useful for diagnosis of cancer. The artifacts and personal detail information's of images are eliminated with pre-processing stages of segmentation. Further, the tumor's edge details can be computed by using various segmentation methods. These segmented results are further diagnosed by the experts. In those segmentation methods this paper works with Hybrid image segmentation and Otsu's thresholding methods. In these methods, the Hybrid image segmentation is based on fast sweeping algorithm and dual front evolution with laplacian or gradient and Otsu's thresholding with 10 threshold levels are used. The combination of these two will give better performance. With this process, the artifacts are to be eliminated and the of Breast cancer tumor are detected. These details provide the size of the tumor and stage of the cancer.