Breast Tumor Segmentation using Image Segmentation Algorithms

Breast tumor is one of the major reason of death among women worldwide. The main objective of this paper is to compare the accuracy of three different algorithms used to detect breast tumors. Comprehending the nature of data set in breast images is essential for evolving a model that fits well into the data. The performance of a traditional k-means algorithm is compared with a much more sophisticated saliency map and colour spacing algorithm. The three algorithms have been applied on a breast tumor MRI scanned image, and the results clearly showed the best performance is yielded.