Paper
14 April 2000 Computer-aided methods to recover strategies for visual search and navigation
Tatjana P. Belikova, Irina I. Stenina, Nadezsda I. Yashunskaya
Author Affiliations +
Abstract
A series of methods developed to recover strategies for visual search and navigation to support image analysis and classification in the case of uncertainty is presented. We used optimal filtering for better imaging of informative features, along with expert descriptions of processed images by the expert in terms of observed features. We collected these data in a database. Expert-guided analysis of the data in the database was applied to find discriminative features important for image interpretation. A formal decision rule was worked out for computer-aided image classification. The developed formal decision rule presented an effective strategy for image analysis and interpretation, orienting the user to look for specific features, and also showing how to classify the image on the basis of observed features. The methods were tested in the task of early peripheral lung cancer diagnosis. Experiments with more than 600 lung tomogram showed that an application of the methods gives essential (by 10% - 16%) improvement of diagnostic accuracy for physicians of different qualifications.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tatjana P. Belikova, Irina I. Stenina, and Nadezsda I. Yashunskaya "Computer-aided methods to recover strategies for visual search and navigation", Proc. SPIE 3981, Medical Imaging 2000: Image Perception and Performance, (14 April 2000); https://doi.org/10.1117/12.383115
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Cited by 1 scholarly publication.
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KEYWORDS
Image processing

Image analysis

Image classification

Databases

Diagnostics

Lung

Medical imaging

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