Medical Image Understanding Technology by Tadeusiewicz, Ryszard;

Artificial Intelligence and Soft-Computing for Image Understanding

Series: Studies in Fuzziness and Soft Computing; 156;

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Product details:

Edition number 2004
Publisher Springer Berlin Heidelberg
Date of Publication 14 May 2004
Number of Volumes 1 pieces, Book

ISBN 9783540219859
Binding Hardback
See also 9783642535789
No. of pages156 pages
Size 235x155 mm
Weight 455 g
Language English
Illustrations VII, 156 p. 133 illus. Illustrations, black & white

Long description:

A detailed description of a new approach to perceptual analysis and processing of medical images is given. Instead of traditional pattern recognition a new method of image analysis is presented, based on a syntactic description of the shapes selected on the image and graph-grammar parsing algorithms. This method of ""Image Understanding"" can be found as a model of mans' cognitive image understanding processes. The usefulness for the automatic understanding of the merit of medical images is demonstrated as well as the ability for giving useful diagnostic descriptions of the illnesses. As an application, the production of a content-based, automatically generated index for arranging and for searching medical images in multimedia medical databases is presented.

1. What is Image Understanding Technology and why do we need it?.- 1.1 Methods of Medical Image Acquisition.- 1.2. Analysis and interpretation of medical images.- 1.3. What new values can add to this scheme ‘automatic understanding’ ?.- 1.4. Areas of applications for the automatic understanding of images.- 2. A General Description of the Fundamental Ideas Behind Automatic Image Understanding.- 2.1. Fundamental assumptions.- 2.2. What does image understanding mean?.- 2.3. Linguistic description of images.- 2.4. The use of graph grammar to cognitive resonance.- 3. Formal Bases for the Semantic Approach to Medical Image Processing Leading to Image Understanding Technology.- 3.1 Fundamentals of syntactic pattern recognition methods.- 3.2 Characteristic features and advantages of structural approaches to medical image semantic analysis.- 4. Examples of Structural Pattern Analysis and Medical Image Understanding Application to Medical Diagnosis.- 4.1. Introduction.- 4.2. Pre-processing Methods Designed to Process Selected Medical Images.- 4.3. Making Lexical Elements for the Syntactic Descriptions of Examined structures.- 4.4. Structural Analysis of Coronary Vessels.- 4.4.1 Syntactic Analysis and Diagnosing Coronary Artery Stenoses.- 4.5. Structural Analysis and Understanding of Lesions in Urinary Tract.- 4.6. Syntactic Methods Supporting the Diagnosis of Pancreatitis and Pancreas Neoplasm.- 4.9. Conclusions.- 5. The application of the Image Understanding Technology to Semantic Organisation and Content-Based Searching in Multimedia Medical Data Bases.- 6. Strengths and Weaknesses of the Image Understanding Technology Compared to Previously Known Approaches.- References.