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

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.