Medical Image Analysis (eBook, ePUB)

Redaktion: Frangi, Alejandro; Sonka, Milan; Prince, Jerry

• Format: ePub

Produktbeschreibung

Medical Image Analysis presents practical knowledge on medical image computing and analysis as written by top educators and experts. This text is a modern, practical, self-contained reference that conveys a mix of fundamental methodological concepts within different medical domains. Sections cover core representations and properties of digital images and image enhancement techniques, advanced image computing methods (including segmentation, registration, motion and shape analysis), machine learning, how medical image computing (MIC) is used in clinical and medical research, and how to identify alternative strategies and employ software tools to solve typical problems in MIC.

• Provides an authoritative description of key concepts and methods
• Includes tutorial-based sections that clearly explain principles and their application to different medical domains
• Presents a representative selection of topics to match a modern and relevant approach to medical image computing

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 584
• Erscheinungstermin: 20. September 2023
• Englisch
• ISBN-13: 9780128136584
• Artikelnr.: 69014989

Autorenporträt

Alejandro (Alex) Frangi is Professor of Biomedical Image Computing at the University of Sheffield (USFD) and affiliated to the Electronic & Electrical Engineering Department. He is also Director of the Center for Computational Imaging and Simulation Technologies in Biomedicine and member of INSIGNEO Institute for in silico Medicine. Prof Frangi is Fellow of IEEE. His main research interests are in medical image computing, medical imaging and image-based computational physiology. Prof. Frangi has edited a book, published 5 editorial articles and over 90 journal papers in key international journals of his research field, as well as more than 120 book chapters and international conference papers. He has twice been Guest Editor of special issues of IEEE Trans on Medical Imaging, one on IEEE Trans Biomed Eng, and one of Medical Image Analysis journal.

Inhaltsangabe

PART I Introductory topics
1. Medical imaging modalities
2. Mathematical preliminaries
3. Regression and classification
4. Estimation and inference
PART II Image representation and processing
5. Image representation and 2D signal processing
6. Image filtering: enhancement and restoration
7. Multiscale and multiresolution analysis
PART III Medical image segmentation
8. Statistical shape models
9. Segmentation by deformable models
10. Graph cut-based segmentation
PART IV Medical image registration
11. Points and surface registration
12. Graph matching and registration
13. Parametric volumetric registration
14. Non-parametric volumetric registration
15. Image mosaicking
PART V Machine learning in medical image analysis
16. Deep learning fundamentals
17. Deep learning for vision and representation learning
18. Deep learning medical image segmentation
19. Machine learning in image registration
PART VI Advanced topics in medical image analysis
20. Motion and deformation recovery and analysis
21. Imaging Genetics
PART VII Large-scale databases
22. Detection and quantitative enumeration of objects from large images
23. Image retrieval in big image data
PART VIII Evaluation in medical image analysis
24. Assessment of image computing methods