A comparison of computer based classification methods applied to the detection of microaneurysms in ophthalmic fluorescein angiograms.
Comput Biol Med
; 28(3): 225-38, 1998 May.
Article
en En
| MEDLINE
| ID: mdl-9784961
ABSTRACT
We compared the performance of three computer based classification methods when applied to the problem of detecting microaneurysms on digitised angiographic images of the retina. An automated image processing system segmented 'candidate' objects (microaneurysms or spurious objects), and produced a list of features on each candidate for use by the classifiers. We compared an empirically derived rule based system with two automated methods, linear discriminant analysis and a learning vector quantiser artificial neural network, to classify the objects as microaneurysms or otherwise. ROC analysis shows that the rule based system gave a higher performance than the other methods (p = 0.92) although a much greater development time is required.
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Banco de datos:
MEDLINE
Asunto principal:
Vasos Retinianos
/
Inteligencia Artificial
/
Angiografía con Fluoresceína
/
Diagnóstico por Computador
/
Aneurisma
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Comput Biol Med
Año:
1998
Tipo del documento:
Article
País de afiliación:
Reino Unido