Clustering of breast cancer tumor using third order GLCM feature

A huge increase in medical image database volume has set new challenges to clinical routine for patients record about diagnosis, treatment & follow -up, with help of data & image mining it is possible to assist or automate the radiologist for diagnosis. Detection of breast cancer is done with mammogram, which are low dose x-ray images. Mammogram images play a very significant role in early detection of breast cancer. Usually in image mining texture analysis is used for clustering and classification based on content of image. Up till now in breast cancer detection only first and second order GLCM features were mostly used, to the best of our knowledge there is no evidence of use of third order features. In this research paper we retrieved a novel third order features and observed the results by clustering the effects of higher order features in recognition of malignancy in a novel breast mammogram´s regional database.