Computer-aided identification of ovarian cancer in confocal microendoscope images.
J Biomed Opt
; 13(2): 024021, 2008.
Article
em En
| MEDLINE
| ID: mdl-18465984
ABSTRACT
The confocal microendoscope is an instrument for imaging the surface of the human ovary. Images taken with this instrument from normal and diseased tissue show significant differences in cellular distribution. A real-time computer-aided system to facilitate the identification of ovarian cancer is introduced. The cellular-level structure present in ex vivo confocal microendoscope images is modeled as texture. Features are extracted based on first-order statistics, spatial gray-level-dependence matrices, and spatial-frequency content. Selection of the features is performed using stepwise discriminant analysis, forward sequential search, a nonparametric method, principal component analysis, and a heuristic technique that combines the results of these other methods. The selected features are used for classification, and the performance of various machine classifiers is compared by analyzing areas under their receiver operating characteristic curves. The machine classifiers studied included linear discriminant analysis, quadratic discriminant analysis, and the k-nearest-neighbor algorithm. The results suggest it is possible to automatically identify pathology based on texture features extracted from confocal microendoscope images and that the machine performance is superior to that of a human observer.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Neoplasias Ovarianas
/
Algoritmos
/
Reconhecimento Automatizado de Padrão
/
Inteligência Artificial
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Interpretação de Imagem Assistida por Computador
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Microscopia Confocal
/
Endoscopia
Tipo de estudo:
Diagnostic_studies
/
Evaluation_studies
/
Prognostic_studies
Limite:
Female
/
Humans
Idioma:
En
Ano de publicação:
2008
Tipo de documento:
Article