Segmentation of overlapping leucocyte images with phase detection and spiral interpolation

Guanghua Gu, Dong Cui and Xiaoli Li

Computer Methods in Biomechanics and Biomedical Engineering, 2012, vol. 15, issue 4, 425-433

Abstract: Leucocyte segmentation is one of the most crucial functionalities for an automatic leucocyte recognition system. In this paper, an algorithm is proposed to segment the leucocytes from the overlapping cell images. It consists of two main steps. The first step involves generation of a combined image based on the saturation and green channels (CIBSGC) by means of the different distribution characteristics of the leucocyte nucleus. A weight coefficient is used to adjust the CIBSGC for extracting the nucleus and estimating the location of the leucocyte. Second, a method of phase detection and spiral interpolation identifies the overlapping regions of cells and determines the leucocyte edge curve. The performance is evaluated by three parameters: sensitivity, positive predictive value and pixel number error. Experimental results validate that the proposed algorithm can successfully segment the overlapping leucocyte with the satisfactory performance for two cell image datasets under different recording conditions.

Date: 2012
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10255842.2010.539565 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:gcmbxx:v:15:y:2012:i:4:p:425-433

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/gcmb20

DOI: 10.1080/10255842.2010.539565

Access Statistics for this article

Computer Methods in Biomechanics and Biomedical Engineering is currently edited by Director of Biomaterials John Middleton

More articles in Computer Methods in Biomechanics and Biomedical Engineering from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().