Authors: Vikramathithan Andiappan Chinnasamy; Dandinashivara Revanna Shashikumar
Addresses: Visvesvaraya Technological University, Karnataka, India ' Department of Computer Science, Cambridge Institute of Technology, India; Department of Computer Science, Visvesvaraya Technological University (VTU), India
Abstract: In our proposed breast cancer malignant detection study are performed with the aid of fuzzy min max neural network technique. Majority of women's are affected in this breast cancer at a early stage the mammogram images are mostly play in a vital role. Initially the input mammogram image smoothened with the aid of adaptive median filer from that smoothened image we are segmenting tissues with the aid of Histon based fuzzy c-means clustering. We are extracting features from that segmented image the features are statistical and semantic features. Then we can identify the malignant region with the aid of these features. The segmented region is maligned or benign using an optimal fuzzy min max neural network with grey wolf optimisation algorithm with the aid of these we will identify a breast cancer region.
Keywords: breast cancer; mammogram; fuzzy min-max; grey wolf; optimisation; segmentation.
International Journal of Medical Engineering and Informatics, 2020 Vol.12 No.1, pp.77 - 94
Received: 07 Mar 2018
Accepted: 13 Apr 2018
Published online: 06 Mar 2020 *