NDLI: White blood nucleus extraction using K-Mean clustering and mathematical morphing

Content Provider	IEEE Xplore Digital Library
Author	Gautam, A. Bhadauria, H.S.
Copyright Year	2014
Description	Author affiliation: Comput. Sci. & Eng., G.B. Pant Eng. Coll. (UTU), Pauri, India (Gautam, A.; Bhadauria, H.S.)
Abstract	The White blood cell detection is most important in detection of various kinds of diseases in human body as it provide valuable information to doctors for diagnosis of diseases. This paper focuses on automatic extraction of leukocytes using image processing techniques such as color segmentation, automatic thresholding and mathematical morphing. We have used the K-Mean clustering for the color based segmentation to detect white blood nucleus on a set of 4806403 images. Since manual segmentation is very tedious, tardy and sometime prone to error, besides that the medical equipments which are used for white blood cells detection are very costly and may not be exist in all the hospitals and clinics, so, the automatic system is preferred. In this paper we firstly apply color based segmentation on images for segmentation of white blood cell and platelets which is most important for localization of nucleus, then converting the segmented image to gray scale. We then analyze the nucleus features of white blood cells by mathematical morphing for removing the platelets from the segmented image and this result in final extraction of white blood nucleus. In this research results obtained give a good accuracy rate as compared to others.
Starting Page	549
Ending Page	554
File Size	1053588
Page Count	6
File Format	PDF
e-ISBN	9781479942367
DOI	10.1109/CONFLUENCE.2014.6949220
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-25
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	White blood cells Mathematical Morphin Image segmentation Color Segmentation Image color analysis Automatic Thresholding Cells (biology) K-Mean clustering White Blood cell Diseases
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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