Full Description
Medical imaging is increasingly at the base of many breakthroughs in biomedical sciences, becoming a fundamental enabling technology of biomedical scientific progress. Medical Image Analysis presents practical knowledge on medical image computing and analysis and is written by top educators and experts in the field. This text is a modern, practical, broad, and self-contained reference that conveys a mix of essential methodological concepts within different medical domains, reflecting the nature of the discipline today, making it suitable as a course text and a self-learning resource.
Contents
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
