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Medical Image Analysis: The MICCAI Society book Series

Editat de Alejandro Frangi, Jerry Prince, Milan Sonka
en Limba Engleză Paperback – 26 sep 2023
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.

  • An authoritative presentation of key concepts and methods from experts in the field
  • Sections clearly explaining key methodological principles within relevant medical applications
  • Self-contained chapters enable the text to be used on courses with differing structures
  • A representative selection of modern topics and techniques in medical image computing
  • Focus on medical image computing as an enabling technology to tackle unmet clinical needs
  • Presentation of traditional and machine learning approaches to medical image computing
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Specificații

ISBN-13: 9780128136577
ISBN-10: 012813657X
Pagini: 698
Dimensiuni: 191 x 235 x 39 mm
Greutate: 1.42 kg
Editura: ELSEVIER SCIENCE
Seria The MICCAI Society book Series


Public țintă

Researchers in Medical Image computing and analysis; Ideal Text-Ref for courses on medical image analysis in BEng/MEng/MSc programs in Biomedical Engineering, Medical Physics, Medical Engineering, or Computational Bioengineering

Cuprins

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