Adaptive neuro-fuzzy inference system for classification of mammographic image using electromagnetism-like optimisation Online publication date: Thu, 15-Feb-2018
by M.N. Vimalkumar; K. Helenprabha
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 26, No. 3/4, 2018
Abstract: Breast cancer diagnosis system plays a vital role in medical field. This system helps the doctors to diagnose in much more efficient way. Breast cancer is a very common class of cancer among women. This paper mainly focuses on breast cancer recurrence problem, hybridising two methodologies; Electro-Magnetism-like Optimisation (EMO) and Adaptive Neuro-Fuzzy Inference System (ANFIS), to develop a good diagnosis system. EMO has been used as a multilevel segmentation algorithm which can effectively identify the threshold values of a digital image within the reduced number of iterations and decreasing the computational complexity. Original proposals show better results in diagnosing cancer affected cells to find the best features, whilst ANFIS algorithm is used as a classifier. ANFIS model combines the neural network adaptive capabilities and the fuzzy logic qualitative approach. The robustness of the proposed hybrid methodology is examined using classification accuracy, sensitivity, and specificity.
Online publication date: Thu, 15-Feb-2018
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Biomedical Engineering and Technology (IJBET):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com