Knowledge-based 3D analysis from 2D medical images.
IEEE Eng Med Biol Mag
; 10(4): 30-7, 1991.
Article
en En
| MEDLINE
| ID: mdl-18238387
ABSTRACT
An anatomical knowledge-based system for image analysis that interprets CT/MR (computed tomography/magnetic resonance) images of the human chest cavity is reported. The approach utilizes a low-level image analysis system with the ability to analyze the data in bottom-up (or data-driven) and top-down (or model-driven) modes to improve the high-level recognition process. Several image segmentation algorithms, including K-means clustering, pyramid-based region extraction, and rule-based merging, are used for obtaining the segmented regions. To obtain a reasonable number of well-segmented regions that have a good correlation with the anatomy, a priori knowledge in the form of masks is used to guide the segmentation process. Segmentation of the brain is also considered.
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Base de datos:
MEDLINE
Idioma:
En
Revista:
IEEE Eng Med Biol Mag
Año:
1991
Tipo del documento:
Article