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Proceedings Paper

Model-based labeling, analysis, and three-dimensional visualization from two-dimensional medical images
Author(s): Louis K. Arata; Atam P. Dhawan; Stephen R. Thomas
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Paper Abstract

The computerized analysis and interpretation of three-dimensional medical images is of significant interest for diagnosis as well as for studying pathological processes. Knowledge-based image analysis and interpretation of radiological images can provide a tool for identifying and labeling each part of the image. The authors have developed a knowledge-based biomedical image analysis system for interpreting medical images using an anatomical knowledge base of the appropriate organs. In this paper, the structure of the biomedical image analysis system, along with results from the analysis of images of the human chest cavity, are presented. This approach utilizes an image analysis system with the capability of analyzing the data in both bottom-up (or data driven) and top-down (or model driven) modes to improve the recognition process. After an initial identification is achieved, segmented regions are aggregated and features for these aggregates are recomputed and matched to the model. This process continues until a 'best' match is found for the subject model region. Initial results are encouraging; however, much work remains to be done.

Paper Details

Date Published: 1 July 1991
PDF: 10 pages
Proc. SPIE 1446, Medical Imaging V: PACS Design and Evaluation, (1 July 1991); doi: 10.1117/12.45306
Show Author Affiliations
Louis K. Arata, Univ. of Cincinnati (United States)
Atam P. Dhawan, Univ. of Cincinnati (United States)
Stephen R. Thomas, Univ. of Cincinnati (United States)

Published in SPIE Proceedings Vol. 1446:
Medical Imaging V: PACS Design and Evaluation

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