| Author | Morais, Mauro César Cafundó | |
| Author | Silva, Diogo | |
| Author | Milagre, Matheus Marques | |
| Author | Oliveira, Maykon Tavares de | |
| Author | Pereira, Thaís | |
| Author | Silva, João Santana | |
| Author | Costa, Luciano da F. | |
| Author | Minoprio, Paola | |
| Author | Cesar Junior, Roberto Marcondes | |
| Author | Gazzinelli, Ricardo Tostes | |
| Author | Lana, Marta de | |
| Author | Nakaya, Helder | |
| Access date | 2022-11-09T19:10:13Z | |
| Available date | 2022-11-09T19:10:13Z | |
| Document date | 2022 | |
| Citation | MORAIS, Mauro César Cafundó et al. Automatic detection of the parasite Trypanosoma cruzi in blood smears using a machine learning approach applied to mobile phone images. PeerJ, v. 10, p. e13470-1-e13470-19, 2022. | en_US |
| ISSN | 2167-8359 | en_US |
| URI | https://www.arca.fiocruz.br/handle/icict/55567 | |
| Language | eng | en_US |
| Publisher | PeerJ Publishing | en_US |
| Rights | open access | en_US |
| Title | Automatic detection of the parasite Trypanosoma cruzi in blood smears using a machine learning approach applied to mobile phone images | en_US |
| Type | Article | en_US |
| DOI | 10.7717/peerj.13470 | |
| Abstract | Chagas disease is a life-threatening illness caused by the parasite Trypanosoma cruzi. The diagnosis of the acute form of the disease is performed by trained microscopists who detect parasites in blood smear samples. Since this method requires a dedicated high-resolution camera system attached to the microscope, the diagnostic method is more expensive and often prohibitive for low-income settings. Here, we present a machine learning approach based on a random forest (RF) algorithm for the detection and counting of T. cruzi trypomastigotes in mobile phone images. We analyzed micrographs of blood smear samples that were acquired using a mobile device camera capable of capturing images in a resolution of 12 megapixels. We extracted a set of features that describe morphometric parameters (geometry and curvature), as well as color, and texture measurements of 1,314 parasites. The features were divided into train and test sets (4:1) and classified using the RF algorithm. The values of precision, sensitivity, and area under the receiver operating characteristic (ROC) curve of the proposed method were 87.6%, 90.5%, and 0.942, respectively. Automating image analysis acquired with a mobile device is a viable alternative for reducing costs and gaining efficiency in the use of the optical microscope | en_US |
| Affilliation | Hospital Israelita Albert Einstein. São Paulo, SP, Brazil / University of São Paulo. Sao Paulo, SP, Brazil / Universidade de São Paulo. School of Pharmaceutical Sciences. Department of Clinical and Toxicological Analysis. São Paulo, SP, Brazil. | en_US |
| Affilliation | Universidade de São Paulo. School of Pharmaceutical Sciences. Department of Clinical and Toxicological Analysis. São Paulo, SP, Brazil. | en_US |
| Affilliation | Universidade Federal de Ouro Preto. Programa de Pós-graduação em Ciências Farmacêuticas. Departamento de Análises Clínicas. Ouro Preto, MG, Brazil. | en_US |
| Affilliation | Fundação Oswaldo Cruz. Fiocruz São Paulo. Bi-Institutional Translational Medicine Project. Ribeirão Preto, SP, Brazil. | en_US |
| Affilliation | Fundação Oswaldo Cruz. Instituto René Rachou. Laboratório de Imunopatologia. Belo Horizonte, MG, Brasil / Universidade Federal de Minas Gerais. Belo Horizonte, MG, Brazil. | en_US |
| Affilliation | Fundação Oswaldo Cruz. Fiocruz São Paulo. Bi-Institutional Translational Medicine Project. Ribeirão Preto, SP, Brazil. | en_US |
| Affilliation | Universidade de São Paulo. São Carlos Institute of Physics. São Carlos, SP, Brazil. | en_US |
| Affilliation | Universidade de São Paulo. Scientific Platform Pasteur-University of São Paulo. Sao Paulo, SP, Brazil. | en_US |
| Affilliation | Universidade de São Paulo. Instituto de Matemática e Estatística. São Paulo, SP, Brazil. | en_US |
| Affilliation | Fundação Oswaldo Cruz. Instituto René Rachou. Laboratório de Imunopatologia. Belo Horizonte, MG, Brasil / Universidade Federal de Minas Gerais. Belo Horizonte, MG, Brazil. | en_US |
| Affilliation | Universidade Federal de Ouro Preto. Programa de Pós-graduação em Ciências Farmacêuticas. Departamento de Análises Clínicas. Ouro Preto, MG, Brazil / Universidade Federal de Ouro Preto. Núcleo de Pesquisas em Ciências Biológicas. Ouro Preto, MG, Brazil. | en_US |
| Affilliation | Hospital Israelita Albert Einstein. São Paulo, SP, Brazil / Universidade de São Paulo. Scientific Platform Pasteur. São Paulo, SP, Brazil / Universidade de São Paulo. School of Pharmaceutical Sciences. Department of Clinical and Toxicological Analysis. São Paulo, SP, Brazil / Universidade de São Paulo. Center of Research in Inflammatory Diseases. Ribeirão Preto, SP, Brazil. | en_US |
| Subject | Blood trypomastigote | en_US |
| Subject | Machine learning | en_US |
| Subject | Parasitemia | en_US |
| Subject | SVM | en_US |
| Subject | Trypanosoma cruzi | en_US |
| xmlui.metadata.dc.subject.ods | 04 Educação de qualidade | |
