Staining pattern classification of antinuclear autoantibodies based on block segmentation in indirect immunofluorescence images.
PLoS One
; 9(12): e113132, 2014.
Article
em En
| MEDLINE
| ID: mdl-25474260
ABSTRACT
Indirect immunofluorescence based on HEp-2 cell substrate is the most commonly used staining method for antinuclear autoantibodies associated with different types of autoimmune pathologies. The aim of this paper is to design an automatic system to identify the staining patterns based on block segmentation compared to the cell segmentation most used in previous research. Various feature descriptors and classifiers are tested and compared in the classification of the staining pattern of blocks and it is found that the technique of the combination of the local binary pattern and the k-nearest neighbor algorithm achieve the best performance. Relying on the results of block pattern classification, experiments on the whole images show that classifier fusion rules are able to identify the staining patterns of the whole well (specimen image) with a total accuracy of about 94.62%.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Doenças Autoimunes
/
Anticorpos Antinucleares
/
Técnica Indireta de Fluorescência para Anticorpo
/
Imagem Óptica
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
PLoS One
Ano de publicação:
2014
Tipo de documento:
Article