Detection and separation of overlapping cells based on contour concavity for Leishmania images

• Type: Article in International Scientific Journal
• Date: 2014

Authors

Joao C Neves (Author) Other; Helena Castro (Author) Other; Ana Tomas (Author) Other; Miguel Coimbra (Author) FCUP; Hugo Proenca (Author) Other

Journal

Title: Cytometry Part A

Vol. 85A

Pages: 491-500

ISSN: 1552-4922

Publisher: Wiley-Blackwell

Indexing

ISI Web of Knowledge - 8 Citations

Scopus - 12 Citations

Other information

Authenticus ID: P-009-HE3

DOI: 10.1002/cyto.a.22465

Abstract (EN): 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 Leishmania-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 Leishmania infections. (c) 2014 International Society for Advancement of Cytometry

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10