Knowledge-based 3D analysis from 2D medical images
Autor: | Louis K. Arata, Atam P. Dhawan |
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Rok vydání: | 1991 |
Předmět: |
Computer science
Segmentation-based object categorization business.industry Biomedical Engineering Scale-space segmentation General Medicine Image segmentation Knowledge-based systems Computer vision Segmentation Pyramid (image processing) Artificial intelligence Range segmentation business Cluster analysis |
Zdroj: | IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in MedicineBiology Society. 10(4) |
ISSN: | 0739-5175 |
Popis: | 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. > |
Databáze: | OpenAIRE |
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