Literature DB >> 24028798

An automatic algorithm for the detection of Trypanosoma cruzi parasites in blood sample images.

Roger Soberanis-Mukul1, Víctor Uc-Cetina, Carlos Brito-Loeza, Hugo Ruiz-Piña.   

Abstract

Chagas disease is a tropical parasitic disease caused by the flagellate protozoan Trypanosoma cruzi (T. cruzi) and currently affecting large portions of the Americas. One of the standard laboratory methods to determine the presence of the parasite is by direct visualization in blood smears stained with some colorant. This method is time-consuming, requires trained microscopists and is prone to human mistakes. In this article we propose a novel algorithm for the automatic detection of T. cruzi parasites, in microscope digital images obtained from peripheral blood smears treated with Wright's stain. Our algorithm achieved a sensitivity of 0.98 and specificity of 0.85 when evaluated against a dataset of 120 test images. Experimental results show the versatility of the method for parasitemia determination.
Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Image detection systems; Medical and biological imaging; Pattern recognition

Mesh:

Year:  2013        PMID: 24028798     DOI: 10.1016/j.cmpb.2013.07.013

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  3 in total

1.  Effective residual convolutional neural network for Chagas disease parasite segmentation.

Authors:  Allan Ojeda-Pat; Anabel Martin-Gonzalez; Carlos Brito-Loeza; Hugo Ruiz-Piña; Daniel Ruz-Suarez
Journal:  Med Biol Eng Comput       Date:  2022-03-01       Impact factor: 2.602

2.  Automatic detection of the parasite Trypanosoma cruzi in blood smears using a machine learning approach applied to mobile phone images.

Authors:  Mauro César Cafundó Morais; Diogo Silva; Matheus Marques Milagre; Maykon Tavares de Oliveira; Thaís Pereira; João Santana Silva; Luciano da F Costa; Paola Minoprio; Roberto Marcondes Cesar Junior; Ricardo Gazzinelli; Marta de Lana; Helder I Nakaya
Journal:  PeerJ       Date:  2022-05-27       Impact factor: 3.061

3.  Chagas parasite detection in blood images using AdaBoost.

Authors:  Víctor Uc-Cetina; Carlos Brito-Loeza; Hugo Ruiz-Piña
Journal:  Comput Math Methods Med       Date:  2015-03-11       Impact factor: 2.238

  3 in total

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