Cric searchable image database as a public platform for conventional pap smear cytology data

Abstract Amidst the current health crisis and social distancing, telemedicine has become an important part of mainstream of healthcare, and building and deploying computational tools to support screening more efficiently is an increasing medical priority. The early identification of cervical cancer...

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Autores principales:	Mariana T. Rezende, Raniere Silva, Fagner de O. Bernardo, Alessandra H. G. Tobias, Paulo H. C. Oliveira, Tales M. Machado, Caio S. Costa, Fatima N. S. Medeiros, Daniela M. Ushizima, Claudia M. Carneiro, Andrea G. C. Bianchi
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/1a2d01d4f41e456ea12047413c935cca
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spelling	oai:doaj.org-article:1a2d01d4f41e456ea12047413c935cca2021-12-02T17:52:43ZCric searchable image database as a public platform for conventional pap smear cytology data10.1038/s41597-021-00933-82052-4463https://doaj.org/article/1a2d01d4f41e456ea12047413c935cca2021-06-01T00:00:00Zhttps://doi.org/10.1038/s41597-021-00933-8https://doaj.org/toc/2052-4463Abstract Amidst the current health crisis and social distancing, telemedicine has become an important part of mainstream of healthcare, and building and deploying computational tools to support screening more efficiently is an increasing medical priority. The early identification of cervical cancer precursor lesions by Pap smear test can identify candidates for subsequent treatment. However, one of the main challenges is the accuracy of the conventional method, often subject to high rates of false negative. While machine learning has been highlighted to reduce the limitations of the test, the absence of high-quality curated datasets has prevented strategies development to improve cervical cancer screening. The Center for Recognition and Inspection of Cells (CRIC) platform enables the creation of CRIC Cervix collection, currently with 400 images (1,376 × 1,020 pixels) curated from conventional Pap smears, with manual classification of 11,534 cells. This collection has the potential to advance current efforts in training and testing machine learning algorithms for the automation of tasks as part of the cytopathological analysis in the routine work of laboratories.Mariana T. RezendeRaniere SilvaFagner de O. BernardoAlessandra H. G. TobiasPaulo H. C. OliveiraTales M. MachadoCaio S. CostaFatima N. S. MedeirosDaniela M. UshizimaClaudia M. CarneiroAndrea G. C. BianchiNature PortfolioarticleScienceQENScientific Data, Vol 8, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Mariana T. Rezende Raniere Silva Fagner de O. Bernardo Alessandra H. G. Tobias Paulo H. C. Oliveira Tales M. Machado Caio S. Costa Fatima N. S. Medeiros Daniela M. Ushizima Claudia M. Carneiro Andrea G. C. Bianchi Cric searchable image database as a public platform for conventional pap smear cytology data
description	Abstract Amidst the current health crisis and social distancing, telemedicine has become an important part of mainstream of healthcare, and building and deploying computational tools to support screening more efficiently is an increasing medical priority. The early identification of cervical cancer precursor lesions by Pap smear test can identify candidates for subsequent treatment. However, one of the main challenges is the accuracy of the conventional method, often subject to high rates of false negative. While machine learning has been highlighted to reduce the limitations of the test, the absence of high-quality curated datasets has prevented strategies development to improve cervical cancer screening. The Center for Recognition and Inspection of Cells (CRIC) platform enables the creation of CRIC Cervix collection, currently with 400 images (1,376 × 1,020 pixels) curated from conventional Pap smears, with manual classification of 11,534 cells. This collection has the potential to advance current efforts in training and testing machine learning algorithms for the automation of tasks as part of the cytopathological analysis in the routine work of laboratories.
format	article
author	Mariana T. Rezende Raniere Silva Fagner de O. Bernardo Alessandra H. G. Tobias Paulo H. C. Oliveira Tales M. Machado Caio S. Costa Fatima N. S. Medeiros Daniela M. Ushizima Claudia M. Carneiro Andrea G. C. Bianchi
author_facet	Mariana T. Rezende Raniere Silva Fagner de O. Bernardo Alessandra H. G. Tobias Paulo H. C. Oliveira Tales M. Machado Caio S. Costa Fatima N. S. Medeiros Daniela M. Ushizima Claudia M. Carneiro Andrea G. C. Bianchi
author_sort	Mariana T. Rezende
title	Cric searchable image database as a public platform for conventional pap smear cytology data
title_short	Cric searchable image database as a public platform for conventional pap smear cytology data
title_full	Cric searchable image database as a public platform for conventional pap smear cytology data
title_fullStr	Cric searchable image database as a public platform for conventional pap smear cytology data
title_full_unstemmed	Cric searchable image database as a public platform for conventional pap smear cytology data
title_sort	cric searchable image database as a public platform for conventional pap smear cytology data
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/1a2d01d4f41e456ea12047413c935cca
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Cric searchable image database as a public platform for conventional pap smear cytology data

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