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Diagnosis of Cryptosporidium spp. by automated image analysis

Grant number: 18/21204-7
Support type:Scholarships in Brazil - Master
Effective date (Start): March 01, 2019
Effective date (End): February 29, 2020
Field of knowledge:Health Sciences - Collective Health - Public Health
Principal researcher:Jancarlo Ferreira Gomes
Grantee:Saulo Hudson Nery Loiola
Home Institution: Faculdade de Ciências Médicas (FCM). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Associated research grant:14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction?, AP.TEM

Abstract

Laboratory validation of Automated Intestinal Parasite Diagnostic System (DAPI) for detection of Cryptosporidium spp. is the general aim of this project. Sequential experiments will be carried out by the purification of fecal samples containing oocysts of this parasite (with molecular confirmation). Then, it will be made a study for the adequacy of TF-Test Coccidia technique to build a bank of 500 images to train the classifier in the DAPI system pattern recognition module to validate the automated imaging diagnosis of this parasitic genus. For this, fecal samples of 1,000 children from pre-schools and their respective dogs will be used. The results obtained will be evaluated by means of statistical comparison between DAPI system and visual analysis using an established manual technique: TF-Test Coccidia. (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
NERY LOIOLA, SAULO HUDSON; GALVAO, FELIPE LEMES; DOS SANTOS, BIANCA MARTINS; ROSA, STEFANY LARYSSA; SOARES, FELIPE AUGUSTO; INACIO, SANDRA VALERIA; NAGASE SUZUKI, CELSO TETSUO; SABADINI, EDVALDO; SARAIVA BRESCIANI, KATIA DENISE; FALCAO, ALEXANDRE XAVIER; GOMES, JANCARLO FERREIRA. Development of New Staining Procedures for Diagnosing Cryptosporidium spp. in Fecal Samples by Computerized Image Analysis. Microscopy and Microanalysis, v. 27, n. 6, p. 1518-1528, DEC 2021. Web of Science Citations: 0.
Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
. Diagnosis of the protozoan Cryptosporidium spp. via digital image analysis. 2021. 71 f. Master's Dissertation - Universidade Estadual de Campinas (UNICAMP). Faculdade de Ciências Médicas.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.