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

Tadeusiewicz, Ryszard

Softcover

ISBN 10: 3642535771 ISBN 13: 9783642535772

Publisher: Springer, 2014

Synopsis

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.- 1.4.1. T-formed area of applications for the automatic understanding of medical images.- 1.4.2. The Automatic understanding of medical images as a tool for the preliminary classification of imaging screening data.- 1.4.3. Automatic understanding in difficult medical problems.- 1.4.4. Automatic understanding of images as a tool for semantic searching in data bases and successful web crawling.- 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.- 3.1.1 Definitions and basic formalisms associated with syntactic pattern recognition methods.- 3.1.2 Principles of syntax analysers operation.- 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.- 4.2.1. A Need to Apply Medical Data Pre-processing.- 4.2.2. Recommended Stages of Medical Data Pre-processing.- 4.2.3. Segmentation and Filtering of Images.- 4.2.4. Skeletonisation of the Analysed Anatomical Structures.- 4.2.5. Analysis of Skeleton Ramifications.- 4.2.6. Smoothing skeletons of the analysed anatomical structures.- 4.2.7. Transformation Straightening the External Contours of Analysed Objects.- 4.2.8. Straightening Transformation Algorithm.- 4.2.9. Basic Advantages of the Proposed Pre-processing Method.- 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.- 4.4.2 Recognition Results Obtained with the Use of Context-free Grammar.- 4.4.3 Conclusion.- 4.5. Structural Analysis and Understanding of Lesions in Urinary Tract.- 4.5.1 Diagnosing Stenosis of the Ureter Lumen.- 4.5.2 Application of Graph Grammar in the Analysis of Renal Pelvis Shape.- 4.6. Syntactic Methods Supporting the Diagnosis of Pancreatitis and Pancreas Neoplasm.- 4.6.1 Context-free Grammar in the Analysis of Shapes of Pancreatic Ducts.- 4.6.2 Languages of Shape Feature Description in the Analysis of Pancreatic Duct Morphology.- 4.6.3 Results of Syntactic Method Analysis of Pancreatic Ducts.- 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.

Edition details

• Publisher: Springer
• Publication date: 2014
• Language: English
• ISBN 10: 3642535771
• ISBN 13: 9783642535772
• Binding: Paperback
• Number of pages: 168