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

• Tipo: Artigo em Revista Científica Internacional
• Data: 2014

Autores

Joao C Neves (Autor) Outra; Helena Castro (Autor) Outra; Ana Tomas (Autor) Outra; Miguel Coimbra (Autor) FCUP; Hugo Proenca (Autor) Outra

Revista

Título: Cytometry Part A

Vol. 85A

Páginas: 491-500

ISSN: 1552-4922

Editora: Wiley-Blackwell

Indexação

ISI Web of Knowledge - 8 Citações

Scopus - 12 Citações

Outras Informações

ID Authenticus: 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

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 10