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J Struct Biol ; 162(3): 368-79, 2008 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-18358741

RESUMEN

In electron tomography the reconstructed density function is typically corrupted by noise and artifacts. Under those conditions, separating the meaningful regions of the reconstructed density function is not trivial. Despite development efforts that specifically target electron tomography manual segmentation continues to be the preferred method. Based on previous good experiences using a segmentation based on fuzzy logic principles (fuzzy segmentation) where the reconstructed density functions also have low signal-to-noise ratio, we applied it to electron tomographic reconstructions. We demonstrate the usefulness of the fuzzy segmentation algorithm evaluating it within the limits of segmenting electron tomograms of selectively stained, plastic embedded spiny dendrites. The results produced by the fuzzy segmentation algorithm within the framework presented are encouraging.


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Tomografía/métodos , Algoritmos , Inteligencia Artificial , Electrones , Lógica Difusa , Humanos , Procesamiento de Imagen Asistido por Computador , Modelos Estadísticos , Variaciones Dependientes del Observador , Reconocimiento de Normas Patrones Automatizadas , Reproducibilidad de los Resultados , Programas Informáticos , Tomografía/instrumentación , Interfaz Usuario-Computador
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