New scheme for breast cancer detection and staging using ant colony algorithm Online publication date: Mon, 09-Jul-2018
by Priyadarshini Velusamy; Porkumaran Karantharaj; S. Prabakar
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 27, No. 1/2, 2018
Abstract: The ant colony optimisation (ACO) is an optimisation technique which first proposed ant-based metaheuristic developed by Marco Dorigo. The stimulating source of ant colony optimisation is a searching behaviour of real ant colonies. The proposed hybrid method consists of an enhanced ACO algorithm Discrete Wavelet Transform (DWT) Principle component analysis (PCA) and TNM (The size of the breast tumour (T), nearby lymph nodes (N), Metastasised (M)) system for detecting the edges of the tumour, feature extraction, feature reduction and tumour staging. For the early detection of breast cancer and staging the proposed analysis has been done with two different image modalities which is mammogram images and PET images.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
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 subs@inderscience.com