Busca avançada
Ano de início
Entree


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

Texto completo
Autor(es):
Mostrar menos -
Cafundo Morais, Mauro Cesar ; Silva, Diogo ; Milagre, Matheus Marques ; de Oliveira, Maykon Tavares ; Pereira, Thais ; Silva, Joao Santana ; Costa, Luciano da F. ; Minoprio, Paola ; Cesar Junior, Roberto Marcondes ; Gazzinelli, Ricardo ; de Lana, Marta ; Nakaya, Helder, I
Número total de Autores: 12
Tipo de documento: Artigo Científico
Fonte: PeerJ; v. 10, p. 19-pg., 2022-05-27.
Resumo

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. (AU)

Processo FAPESP: 20/12017-9 - Aprendizado de máquina para interpretação de análise de imagens microscópicas
Beneficiário:Mauro César Cafundó de Morais
Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
Processo FAPESP: 18/14933-2 - Biologia integrativa aplicada à saúde humana
Beneficiário:Helder Takashi Imoto Nakaya
Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores - Fase 2