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OralImmunoAnalyser: a software tool for immunohistochemical assessment of oral leukoplakia using image segmentation and classification models.
Al-Tarawneh, Zakaria A; Pena-Cristóbal, Maite; Cernadas, Eva; Suarez-Peñaranda, José Manuel; Fernández-Delgado, Manuel; Mbaidin, Almoutaz; Gallas-Torreira, Mercedes; Gándara-Vila, Pilar.
Afiliação
  • Al-Tarawneh ZA; Computer Science Department, Mutah University, Karak, Jordan.
  • Pena-Cristóbal M; Centro Singular de Investigación en Tecnoloxías Intelixentes da USC, Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain.
  • Cernadas E; Oral Medicine, Oral Surgery and Implantology Unit, MedOralRes Group of University of Santiago, Santiago de Compostela, Spain.
  • Suarez-Peñaranda JM; Centro Singular de Investigación en Tecnoloxías Intelixentes da USC, Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain.
  • Fernández-Delgado M; Pathological Anatomy Service, University Hospital Complex of Santiago (CHUS), Santiago de Compostela, Spain.
  • Mbaidin A; Department of Forensic Sciences and Pathology, University of Santiago, Santiago de Compostela, Spain.
  • Gallas-Torreira M; Centro Singular de Investigación en Tecnoloxías Intelixentes da USC, Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain.
  • Gándara-Vila P; Computer Science Department, Mutah University, Karak, Jordan.
Front Artif Intell ; 7: 1324410, 2024.
Article em En | MEDLINE | ID: mdl-38469158
ABSTRACT
Oral cancer ranks sixteenth amongst types of cancer by number of deaths. Many oral cancers are developed from potentially malignant disorders such as oral leukoplakia, whose most frequent predictor is the presence of epithelial dysplasia. Immunohistochemical staining using cell proliferation biomarkers such as ki67 is a complementary technique to improve the diagnosis and prognosis of oral leukoplakia. The cell counting of these images was traditionally done manually, which is time-consuming and not very reproducible due to intra- and inter-observer variability. The software presently available is not suitable for this task. This article presents the OralImmunoAnalyser software (registered by the University of Santiago de Compostela-USC), which combines automatic image processing with a friendly graphical user interface that allows investigators to oversee and easily correct the automatically recognized cells before quantification. OralImmunoAnalyser is able to count the number of cells in three staining levels and each epithelial layer. Operating in the daily work of the Odontology Faculty, it registered a sensitivity of 64.4% and specificity of 93% for automatic cell detection, with an accuracy of 79.8% for cell classification. Although expert supervision is needed before quantification, OIA reduces the expert analysis time by 56.5% compared to manual counting, avoiding mistakes because the user can check the cells counted. Hence, the SUS questionnaire reported a mean score of 80.9, which means that the system was perceived from good to excellent. OralImmunoAnalyser is accurate, trustworthy, and easy to use in daily practice in biomedical labs. The software, for Windows and Linux, with the images used in this study, can be downloaded from https//citius.usc.es/transferencia/software/oralimmunoanalyser for research purposes upon acceptance.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Artif Intell Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Jordânia

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Artif Intell Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Jordânia
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