Bone segmentation in human CT images / 生物医学工程学杂志
Journal of Biomedical Engineering
; (6): 169-173, 2004.
Article
en Zh
| WPRIM
| ID: wpr-291157
Biblioteca responsable:
WPRO
ABSTRACT
In 3D visualization of human skeleton, distinguishing bones from soft tissue in 2D CT slides is the first and most critical procedure. This article presents the methods for image pre-processing, segmentation and smoothing. 1733 CT images of human body from Visible Human Project provided by the American National Library of Medicine are treated in this paper. We use the technique of Chebyshev uniform approximation filtering for denoising and present a new simple adaptive threshold method in segmentation, which combines the similarity of consecutive slices with the region-growing method. In post-processing, we use the algorithms of mathematical morphology and multi-resolution filtering. The accuracy of segmentation is examined and certified by comparing the segmented images with the original one. The results also demonstrate a wide applicability of the method.
Texto completo:
1
Índice:
WPRIM
Asunto principal:
Esqueleto
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Huesos
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Algoritmos
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Procesamiento de Imagen Asistido por Computador
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Diagnóstico por Imagen
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Tomografía Computarizada por Rayos X
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Fantasmas de Imagen
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Anatomía Transversal
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Imagenología Tridimensional
Tipo de estudio:
Diagnostic_studies
Límite:
Humans
Idioma:
Zh
Revista:
Journal of Biomedical Engineering
Año:
2004
Tipo del documento:
Article