Fast leukocyte image segmentation using shadowed sets
by Subrajeet Mohapatra; Dipti Patra; Kundan Kumar
International Journal of Computational Biology and Drug Design (IJCBDD), Vol. 5, No. 1, 2012

Abstract: Leukocyte image segmentation acts as the foundation for all automated image based hematological disease recognition systems. Perfection in image segmentation is a necessary condition for improving the diagnostic accuracy in automated cytology. Even though much effort has been put in developing suitable segmentation routines, the problem still remains open in areas like pathological imaging. Clustering is an essential image segmentation procedure which segments an image into desired regions. This paper introduces a novel Shadowed C-means (SCM) clustering approach towards leukocyte segmentation in blood microscopic images. The segmented nucleus and cytoplasm of a leukocyte can be used for feature extraction which can lead to acute leukemia detection. Absence of parameter tuning in SCM with acceptable segmentation performance gives the proposed scheme an edge over standard cluster based segmentation techniques. Comparative analysis reveals that the proposed algorithm is fast and robust in segmenting stained blood microscopic images in the presence of outliers.

Online publication date: Fri, 05-Dec-2014

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 Computational Biology and Drug Design (IJCBDD):
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