Detection and separation of overlapping cells based on contour concavity for Leishmania images. Issue 6 (9th April 2014)

• Record Type: Journal Article
• Authors: Neves, João C.; Castro, Helena; Tomás, Ana; Coimbra, Miguel; Proença, Hugo; Vereb, György
• Is Part Of: Cytometry. Volume 85:Issue 6(2014:Jun.)
• Page Start: 491
• Page End: 500
• Publication Date: 2014-04-09
• Subjects: Flow cytometry -- Periodicals; Imaging systems in biology -- Periodicals; Imaging systems in medicine -- Periodicals; Diagnostic imaging -- Periodicals; 571.605
• DOI: 10.1002/cyto.a.22465
• Languages: English
• ISSNs: 1552-4922

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>Life scientists often must count cells in microscopy images, which is a tedious and time‐consuming task. Automatic approaches present a solution to this problem. Several procedures have been devised for this task, but the majority suffer from performance degradation in the case of cell overlap. In this article, we propose a method to determine the positions of macrophages and parasites in fluorescence images of <italic>Leishmania</italic>‐infected macrophages. The proposed strategy is primarily based on blob detection, clustering, and separation using concave regions of the cells' contours. In comparison with the approaches of Nogueira (Master's thesis, Department of University of Porto Computer Science, 2011) and Leal et al. (Proceedings of the 9th international conference on Image Analysis and Recognition, Vol. II, ICIAR'12. Berlin, Heidelberg: Springer‐Verlag; 2012. pp. 432–439), which also addressed this type of image, we conclude that the proposed methodology achieves better performance in the automatic annotation of <italic>Leishmania</italic> infections. © 2014 International Society for Advancement of Cytometry</p> </abstract>