Colour Feature Extraction and Polynomial Algorithm for Classification of Lymphoma Images

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorFederal Institute of Triângulo Mineiro-
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.contributorFederal University of ABC-
Autor(es): dc.contributorUniversidade Federal de Uberlândia (UFU)-
Autor(es): dc.creatorMartins, Alessandro S.-
Autor(es): dc.creatorNeves, Leandro A. [UNESP]-
Autor(es): dc.creatorFaria, Paulo R.-
Autor(es): dc.creatorTosta, Thaína A. A.-
Autor(es): dc.creatorBruno, Daniel O. T.-
Autor(es): dc.creatorLongo, Leonardo C. [UNESP]-
Autor(es): dc.creatordo Nascimento, Marcelo Zanchetta-
Data de aceite: dc.date.accessioned2022-02-22T00:23:54Z-
Data de disponibilização: dc.date.available2022-02-22T00:23:54Z-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2019-01-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1007/978-3-030-33904-3_24-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/198207-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/198207-
Descrição: dc.descriptionLymphomas are neoplasms that originate in the lymphatic system and represent one of the most common types of cancer found in the World population. The feature analysis may contribute toward results of higher relevance in the classification of the lesions. Feature extraction methods are employed to obtain data that can indicate lymphoma incidence. In this work, we investigated the multiscale and multidimensional fractal geometry with colour channels and colour models for classification of lymphoma tissue images. The fractal features were extracted from the RGB and LAB models and colour channels. The fractal features were concatenated to form the feature vector. Finally, we employed the Hermite polynomial classifier in order to evaluate the performance of the proposed approach. The colour channels obtained of histological images achieved higher accuracy values, the obtained rates were between 94% and 97%. These results are relevant, especially when we consider the difficulties of clinical practice in distinguishing the lesion in lymphoma images.-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG)-
Descrição: dc.descriptionFederal Institute of Triângulo Mineiro-
Descrição: dc.descriptionDepartment of Computer Science and Statistics (UNESP) São Paulo State University-
Descrição: dc.descriptionCenter of Mathematics Computing and Cognition Federal University of ABC-
Descrição: dc.descriptionDepartment of Histology and Morphology Institute of Biomedical Science Federal University of Uberlândia-
Descrição: dc.descriptionFaculty of Computer Science Federal University of Uberlândia-
Descrição: dc.descriptionDepartment of Computer Science and Statistics (UNESP) São Paulo State University-
Descrição: dc.descriptionCNPq: 304848/2018-2-
Descrição: dc.descriptionCNPq: 313365/2018-0-
Descrição: dc.descriptionCNPq: 427114/2016-0-
Descrição: dc.descriptionCNPq: 430965/2018-4-
Descrição: dc.descriptionFAPEMIG: APQ-00578-18-
Formato: dc.format262-271-
Idioma: dc.languageen-
Relação: dc.relationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectClassification-
Palavras-chave: dc.subjectColour fractal-
Palavras-chave: dc.subjectHermite polynomial-
Palavras-chave: dc.subjectLymphoma-
Título: dc.titleColour Feature Extraction and Polynomial Algorithm for Classification of Lymphoma Images-
Aparece nas coleções:Repositório Institucional - Unesp

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