Evaluation of statistical and Haralick texture features for lymphoma histological images classification

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Federal do ABC (UFABC)-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorUniversidade Federal de Uberlândia (UFU)-
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.creatorAzevedo Tosta, Thaína A.-
Autor(es): dc.creatorde Faria, Paulo R.-
Autor(es): dc.creatorNeves, Leandro A. [UNESP]-
Autor(es): dc.creatordo Nascimento, Marcelo Z.-
Data de aceite: dc.date.accessioned2022-02-22T00:46:11Z-
Data de disponibilização: dc.date.available2022-02-22T00:46:11Z-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2020-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1080/21681163.2021.1902401-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/206110-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/206110-
Descrição: dc.descriptionThe investigation of different types of cancer can be performed by images classification with features extracted from specific regions identified by a segmentation step. Therefore, this study presents the evaluation of texture features extracted from neoplastic nuclei for the classification of lymphomas images. The neoplastic nuclei were segmented by steps of pre and post-processing and a thresholding. Statistical and Haralick’s features extracted from wavelet and ranklet transforms were evaluated with different classifiers. The use of the statistical metrics from the wavelet transform in association with the K-nearest neighbour classifier provided the best results in most of the two-class classifications.-
Descrição: dc.descriptionCenter of Mathematics Computer Science and Cognition Federal University of ABC (UFABC)-
Descrição: dc.descriptionScience and Technology Institute Federal University of São Paulo (UNIFESP)-
Descrição: dc.descriptionDepartment of Histology and Morphology Institute of Biomedical Science Federal University of Uberlândia (UFU)-
Descrição: dc.descriptionDepartment of Computer Science and Statistics São Paulo State University (UNESP)-
Descrição: dc.descriptionFaculty of Computer Science Federal University of Uberlândia (UFU)-
Descrição: dc.descriptionDepartment of Computer Science and Statistics São Paulo State University (UNESP)-
Idioma: dc.languageen-
Relação: dc.relationComputer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization-
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Palavras-chave: dc.subjectclassification-
Palavras-chave: dc.subjectLymphoma histological images-
Palavras-chave: dc.subjectnuclear segmentation-
Palavras-chave: dc.subjecttexture features-
Palavras-chave: dc.subjectwavelet and ranklet transforms-
Título: dc.titleEvaluation of statistical and Haralick texture features for lymphoma histological images classification-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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