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...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-06-01
|
| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340923002470 |
| _version_ | 1797798047724339200 |
|---|---|
| author | Maria Clara Falcão Ribeiro-de-Assis Júlia Pessini Soares Leandro Muniz de Lima Liliana Aparecida Pimenta de Barros Tânia Regina Grão-Velloso Renato A. Krohling Danielle Resende Camisasca |
| author_facet | Maria Clara Falcão Ribeiro-de-Assis Júlia Pessini Soares Leandro Muniz de Lima Liliana Aparecida Pimenta de Barros Tânia Regina Grão-Velloso Renato A. Krohling Danielle Resende Camisasca |
| author_sort | Maria Clara Falcão Ribeiro-de-Assis |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-13T03:57:34Z |
| format | Article |
| id | doaj.art-104a27231df44e898e0f22d031032cf5 |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-03-13T03:57:34Z |
| publishDate | 2023-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-104a27231df44e898e0f22d031032cf52023-06-22T05:03:41ZengElsevierData in Brief2352-34092023-06-0148109128NDB-UFES: An oral cancer and leukoplakia dataset composed of histopathological images and patient dataMaria Clara Falcão Ribeiro-de-Assis0Júlia Pessini Soares1Leandro Muniz de Lima2Liliana Aparecida Pimenta de Barros3Tânia Regina Grão-Velloso4Renato A. Krohling5Danielle Resende Camisasca6School of Dentistry, Clinical Dentistry Departament, Federal University of Espirito Santo, Vitoria, BrazilSchool of Dentistry, Clinical Dentistry Departament, Federal University of Espirito Santo, Vitoria, BrazilNature-inspired Computing Lab, Federal University of Espirito Santo, Vitoria, Brazil; Graduate Program in Computer Science, Federal University of Espirito Santo, Vitoria, BrazilSchool of Dentistry, Clinical Dentistry Departament, Federal University of Espirito Santo, Vitoria, Brazil; Graduate Program in Science Dentistry, Federal University of Espirito Santo, Vitoria, BrazilSchool of Dentistry, Clinical Dentistry Departament, Federal University of Espirito Santo, Vitoria, Brazil; Graduate Program in Science Dentistry, Federal University of Espirito Santo, Vitoria, BrazilNature-inspired Computing Lab, Federal University of Espirito Santo, Vitoria, Brazil; Graduate Program in Computer Science, Federal University of Espirito Santo, Vitoria, BrazilSchool of Dentistry, Clinical Dentistry Departament, Federal University of Espirito Santo, Vitoria, Brazil; Graduate Program in Science Dentistry, Federal University of Espirito Santo, Vitoria, Brazil; Corresponding author at: IOUFES – Ambulatório 4 - Patologia Oral, Avenida Marechal Campos, 1.355, Bairro Santos Dumont, Vitória – ES. CEP: 29042-715The 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.http://www.sciencedirect.com/science/article/pii/S2352340923002470Mouth diseasesSquamous Cell carcinomaOral leukoplakiaDatasetInformation sources |
| spellingShingle | Maria Clara Falcão Ribeiro-de-Assis Júlia Pessini Soares Leandro Muniz de Lima Liliana Aparecida Pimenta de Barros Tânia Regina Grão-Velloso Renato A. Krohling Danielle Resende Camisasca NDB-UFES: An oral cancer and leukoplakia dataset composed of histopathological images and patient data Data in Brief Mouth diseases Squamous Cell carcinoma Oral leukoplakia Dataset Information sources |
| 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 | Mouth diseases Squamous Cell carcinoma Oral leukoplakia Dataset Information sources |
| url | http://www.sciencedirect.com/science/article/pii/S2352340923002470 |
| work_keys_str_mv | AT mariaclarafalcaoribeirodeassis ndbufesanoralcancerandleukoplakiadatasetcomposedofhistopathologicalimagesandpatientdata AT juliapessinisoares ndbufesanoralcancerandleukoplakiadatasetcomposedofhistopathologicalimagesandpatientdata AT leandromunizdelima ndbufesanoralcancerandleukoplakiadatasetcomposedofhistopathologicalimagesandpatientdata AT lilianaaparecidapimentadebarros ndbufesanoralcancerandleukoplakiadatasetcomposedofhistopathologicalimagesandpatientdata AT taniareginagraovelloso ndbufesanoralcancerandleukoplakiadatasetcomposedofhistopathologicalimagesandpatientdata AT renatoakrohling ndbufesanoralcancerandleukoplakiadatasetcomposedofhistopathologicalimagesandpatientdata AT danielleresendecamisasca ndbufesanoralcancerandleukoplakiadatasetcomposedofhistopathologicalimagesandpatientdata |