Image classification of microscopic colonic images using textural properties and KSOM
by Laurence A. Gan Lim, Raouf N.G. Naguib, Elmer P. Dadios, Jose Maria C. Avila
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 3, No. 3/4, 2010

Abstract: Colorectal cancer is considered the third most common neoplasm in the world. Traditionally, pathologists use a microscope to examine histopathological images of biopsy samples taken from patients and make judgments based on their professional expertise. Since this procedure is performed by a human expert, it is therefore subject to inconsistencies due to factors that might affect human performance. To overcome this problem, this paper proposes the use of Kohonen self-organising map and Haralick texture in the analysis of microscopic colonic images. The results presented here are preliminary and show great promise.

Online publication date: Tue, 13-Apr-2010

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
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:

Username:        Password:          Forgotten your 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