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Proceedings Paper

Image processing and syndrome feature analysis to improve image interpretation
Author(s): Tatjana P. Belikova; Irina I. Stenina; Nadezsda I. Yashunskaya
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Paper Abstract

A series of methods have been developed, which are to support medial image analysis and interpretation in the case of data uncertainty and the lack of information for reliable and correct image interpretation. The methods allow the better representation of informative features for expert's analysis; they use the expert's domain knowledge and help to recover new knowledge from the database of processed image descriptions. Created formal decision rules for image analysis and interpretation imitate human argumentation, and present the solution in easily interpretable form. Developed methods have been applied for early peripheral lung cancer diagnosis. Their use helped to enhance expert's diagnostic abilities and essentially improved results of medical image analysis and decision-making for the experts of different qualifications. Developed methods were useful for correct diagnosis of small radiography indeterminate pulmonary opacities. They supported expert's interpretation of conventional and computed tomography images in the case of uncertainty.

Paper Details

Date Published: 10 March 1998
PDF: 7 pages
Proc. SPIE 3348, Optical Information Science and Technology (OIST97): Computer and Holographic Optics and Image Processing, (10 March 1998); doi: 10.1117/12.302493
Show Author Affiliations
Tatjana P. Belikova, Institute for Information Transmission Problems (Russia)
Irina I. Stenina, Institute for Information Transmission Problems (Russia)
Nadezsda I. Yashunskaya, Moscow Medical Academy (Russia)


Published in SPIE Proceedings Vol. 3348:
Optical Information Science and Technology (OIST97): Computer and Holographic Optics and Image Processing
Andrei L. Mikaelian, Editor(s)

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