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NDB-UFES: An oral cancer and leukoplakia dataset composed of histopathological images and patient data

The gold standard for the diagnosis of oral cancer is the microscopic analysis of specimens removed preferentially through incisional biopsies of oral mucosa with a clinically detected suspicious lesion. This dataset contains captured histopathological images of oral squamous cell carcinoma and leuk...

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Autores principales: Ribeiro-de-Assis, Maria Clara Falcão, Soares, Júlia Pessini, de Lima, Leandro Muniz, de Barros, Liliana Aparecida Pimenta, Grão-Velloso, Tânia Regina, Krohling, Renato A., Camisasca, Danielle Resende
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10139872/
https://www.ncbi.nlm.nih.gov/pubmed/37122923
http://dx.doi.org/10.1016/j.dib.2023.109128
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author Ribeiro-de-Assis, Maria Clara Falcão
Soares, Júlia Pessini
de Lima, Leandro Muniz
de Barros, Liliana Aparecida Pimenta
Grão-Velloso, Tânia Regina
Krohling, Renato A.
Camisasca, Danielle Resende
author_facet Ribeiro-de-Assis, Maria Clara Falcão
Soares, Júlia Pessini
de Lima, Leandro Muniz
de Barros, Liliana Aparecida Pimenta
Grão-Velloso, Tânia Regina
Krohling, Renato A.
Camisasca, Danielle Resende
author_sort Ribeiro-de-Assis, Maria Clara Falcão
collection PubMed
description The gold standard for the diagnosis of oral cancer is the microscopic analysis of specimens removed preferentially through incisional biopsies of oral mucosa with a clinically detected suspicious lesion. This dataset contains captured histopathological images of oral squamous cell carcinoma and leukoplakia. A total of 237 images were captured, 89 leukoplakia with dysplasia images, 57 leukoplakia without dysplasia images and 91 carcinoma images. The images were captured with an optical light microscope, using 10x and 40x objectives, attached to a microscope camera and visualized through a software. The images were saved in PNG format at 2048 × 1536 size pixels and they refer to hematoxylin-eosin stained histopathologic slides from biopsies performed between 2010 and 2021 in patients managed at the Oral Diagnosis project (NDB) of the Federal University of Espírito Santo (UFES). Oral leukoplakias were represented by samples with and without epithelial dysplasia. Since the diagnosis considers socio-demographic data (gender, age and skin color) as well as clinical data (tobacco use, alcohol consumption, sun exposure, fundamental lesion, type of biopsy, lesion color, lesion surface and lesion diagnosis), this information was also collected. So, our aim by releasing this dataset NDB-UFES is to provide a new dataset to be used by researchers in Artificial Intelligence (machine and deep learning) to develop tools to assist clinicians and pathologists in the automated diagnosis of oral potentially malignant disorders and oral squamous cell carcinoma.
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spelling pubmed-101398722023-04-29 NDB-UFES: An oral cancer and leukoplakia dataset composed of histopathological images and patient data Ribeiro-de-Assis, Maria Clara Falcão Soares, Júlia Pessini de Lima, Leandro Muniz de Barros, Liliana Aparecida Pimenta Grão-Velloso, Tânia Regina Krohling, Renato A. Camisasca, Danielle Resende Data Brief Data Article The gold standard for the diagnosis of oral cancer is the microscopic analysis of specimens removed preferentially through incisional biopsies of oral mucosa with a clinically detected suspicious lesion. This dataset contains captured histopathological images of oral squamous cell carcinoma and leukoplakia. A total of 237 images were captured, 89 leukoplakia with dysplasia images, 57 leukoplakia without dysplasia images and 91 carcinoma images. The images were captured with an optical light microscope, using 10x and 40x objectives, attached to a microscope camera and visualized through a software. The images were saved in PNG format at 2048 × 1536 size pixels and they refer to hematoxylin-eosin stained histopathologic slides from biopsies performed between 2010 and 2021 in patients managed at the Oral Diagnosis project (NDB) of the Federal University of Espírito Santo (UFES). Oral leukoplakias were represented by samples with and without epithelial dysplasia. Since the diagnosis considers socio-demographic data (gender, age and skin color) as well as clinical data (tobacco use, alcohol consumption, sun exposure, fundamental lesion, type of biopsy, lesion color, lesion surface and lesion diagnosis), this information was also collected. So, our aim by releasing this dataset NDB-UFES is to provide a new dataset to be used by researchers in Artificial Intelligence (machine and deep learning) to develop tools to assist clinicians and pathologists in the automated diagnosis of oral potentially malignant disorders and oral squamous cell carcinoma. Elsevier 2023-04-07 /pmc/articles/PMC10139872/ /pubmed/37122923 http://dx.doi.org/10.1016/j.dib.2023.109128 Text en © 2023 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Ribeiro-de-Assis, Maria Clara Falcão
Soares, Júlia Pessini
de Lima, Leandro Muniz
de Barros, Liliana Aparecida Pimenta
Grão-Velloso, Tânia Regina
Krohling, Renato A.
Camisasca, Danielle Resende
NDB-UFES: An oral cancer and leukoplakia dataset composed of histopathological images and patient data
title NDB-UFES: An oral cancer and leukoplakia dataset composed of histopathological images and patient data
title_full NDB-UFES: An oral cancer and leukoplakia dataset composed of histopathological images and patient data
title_fullStr NDB-UFES: An oral cancer and leukoplakia dataset composed of histopathological images and patient data
title_full_unstemmed NDB-UFES: An oral cancer and leukoplakia dataset composed of histopathological images and patient data
title_short NDB-UFES: An oral cancer and leukoplakia dataset composed of histopathological images and patient data
title_sort ndb-ufes: an oral cancer and leukoplakia dataset composed of histopathological images and patient data
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10139872/
https://www.ncbi.nlm.nih.gov/pubmed/37122923
http://dx.doi.org/10.1016/j.dib.2023.109128
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