Evaluation of statistical and Haralick texture features for lymphoma histological images classification
| Autor: | Marcelo Zanchetta do Nascimento, Thaina A. A. Tosta, Paulo Rogério de Faria, Leandro Alves Neves |
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| Přispěvatelé: | Universidade Federal do ABC (UFABC), Universidade de São Paulo (USP), Universidade Federal de Uberlândia (UFU), Universidade Estadual Paulista (Unesp) |
| Rok vydání: | 2021 |
| Předmět: |
wavelet and ranklet transforms
Computer science Biomedical Engineering Computational Mechanics 02 engineering and technology nuclear segmentation Texture (geology) 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine 0202 electrical engineering electronic engineering information engineering medicine Radiology Nuclear Medicine and imaging Segmentation Lymphoma histological images business.industry fungi food and beverages Cancer Pattern recognition medicine.disease Computer Science Applications classification 020201 artificial intelligence & image processing texture features Artificial intelligence business |
| Zdroj: | Scopus Repositório Institucional da UNESP Universidade Estadual Paulista (UNESP) instacron:UNESP |
| ISSN: | 2168-1171 2168-1163 |
| DOI: | 10.1080/21681163.2021.1902401 |
| Popis: | Made available in DSpace on 2021-06-25T10:26:43Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-01-01 The 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. Center of Mathematics Computer Science and Cognition Federal University of ABC (UFABC) Science and Technology Institute Federal University of São Paulo (UNIFESP) Department of Histology and Morphology Institute of Biomedical Science Federal University of Uberlândia (UFU) Department of Computer Science and Statistics São Paulo State University (UNESP) Faculty of Computer Science Federal University of Uberlândia (UFU) Department of Computer Science and Statistics São Paulo State University (UNESP) |
| Databáze: | OpenAIRE |
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