Classification of H&E images exploring ensemble learning with two-stage feature selection

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversidade Federal de Uberlândia (UFU)-
Autor(es): dc.creatorTenguam, Jaqueline Junko-
Autor(es): dc.creatorDa Costa Longo, Leonardo Henrique-
Autor(es): dc.creatorSilva, Adriano Barbosa-
Autor(es): dc.creatorDe Faria, Paulo Rogerio-
Autor(es): dc.creatorDo Nascimento, Marcelo Zanchetta-
Autor(es): dc.creatorNeves, Leandro Alves-
Data de aceite: dc.date.accessioned2025-08-21T17:47:20Z-
Data de disponibilização: dc.date.available2025-08-21T17:47:20Z-
Data de envio: dc.date.issued2023-03-01-
Data de envio: dc.date.issued2023-03-01-
Data de envio: dc.date.issued2021-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/IWSSIP55020.2022.9854418-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/241593-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/241593-
Descrição: dc.descriptionIn this work, an investigation based on ensemble learning is presented for the recognition of patterns in histological tissues stained with Hematoxylin and Eosin, representative of breast cancer, colorectal cancer, liver tissues and oral dysplasia. The strategy considered compositions with multiple descriptors, such as deep learned and handcrafted, and multiple classifiers. The deep learned descriptors were calculated by exploring different architectures of convolutional neural networks. The handcrafted descriptors were representative of the multidimensional and multiscale fractal categories, Haralick and local binary pattern. The main combinations were obtained through two-stage feature selection (ranking with wrapper selection) and classified via an ensemble composed of five classifiers. The accuracy rates were values between 93.10% and 100%, with some highlights involving the main combinations of approaches.-
Descrição: dc.descriptionSão Paulo State University (UNESP) Dept. of Computer Science and Statistics (DCCE), Sao José do Rio Preto-
Descrição: dc.descriptionFederal University of Uberlândia (UFU) Faculty of Computer Science (FACOM)-
Descrição: dc.descriptionInstitute of Biomedical Science Federal University of Uberlândia (UFU) Dept. of Histology and Morphology-
Descrição: dc.descriptionSão Paulo State University (UNESP) Dept. of Computer Science and Statistics (DCCE), Sao José do Rio Preto-
Idioma: dc.languageen-
Relação: dc.relationInternational Conference on Systems, Signals, and Image Processing-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectensemble learning-
Palavras-chave: dc.subjectfeature selection-
Palavras-chave: dc.subjecthistological images-
Palavras-chave: dc.subjectranking with metaheuristics-
Título: dc.titleClassification of H&E images exploring ensemble learning with two-stage feature selection-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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