Medical Image Understanding Technology Artificial Intelligence and Soft-Computing for Image Understanding /

• Κύριος συγγραφέας: Tadeusiewicz, Ryszard (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2004.
• Έκδοση: 1st ed. 2004.
• Σειρά: Studies in Fuzziness and Soft Computing, 156
• Θέματα: Internal medicine.; Artificial intelligence.; Biomedical engineering.; Pattern recognition.; Biomathematics.; Applied mathematics.; Engineering mathematics.; Internal Medicine.; Artificial Intelligence.; Biomedical Engineering and Bioengineering.; Pattern Recognition.; Physiological, Cellular and Medical Topics.; Mathematical and Computational Engineering.

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...

Πίνακας περιεχομένων:

• 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.