Computer Aided Intervention and Diagnostics in Clinical and Medical Images, 1st ed. 2019 Lecture Notes in Computational Vision and Biomechanics Series, Vol. 31

This book is a compendium of the ICCMIA 2018 proceedings, which provides an ideal reference for all medical imaging researchers and professionals to explore innovative methods and analyses on imaging technologies for better prospective patient care.

This work serves as an exclusive source for new computer assisted clinical and medical developments in imaging diagnosis, intervention and analysis. It includes articles on computer assisted medical scanning techniques, computer-aided diagnosis, robotic surgery and imaging, imaging genomics, clinically-oriented imaging physics and informatics, augmented-reality medical visualization, imaging modalities, computerized radiology, oncology, and surgery. Moreover, information on non-medical imaging that has medical applications such as multi-photon microscopy and confocal, photoacoustic imaging, optical microendoscope, infra-red radiation, and other imaging modalities is also represented.

Chapter 1. Introduction.- Chapter 2. Advances in Computer aided diagnostics on Clinical and Medical Images.- Chapter 3. Data Compression and Anonimisation.- Chapter 4. Human Computer Interaction.- Chapter 5. Intelligent Imaging Systems.- Chapter 6. Motion and Shape Analysis.- Chapter 7. Super-resolution algorithms.- Chapter 8. Statistical Methods in Imaging.- Chapter 9. Clinical and Scientific Evaluation of Imaging Studies.- Chapter 10. Imaging physics, systems analysis and modeling.- Chapter 11. X-ray imaging and computed tomography.- Chapter 12. Ultrasonic acquisition and processing.- Chapter 13. Magnetic resonance imaging (MRI).- Chapter 14. Molecular imaging.- Chapter 15. Digital pathology.- Chapter 16. Emerging image acquisition technologies.- Chapter 17. Tomographic image reconstruction.- Chapter 18. Quantitative imaging.- Chapter 19. Image processing and analysis.- Chapter 20. Computer-aided detection and diagnosis.- Chapter 21. Computational models.- Chapter 22. Image-guided therapies.- Chapter 23. Visual rendering of complex datasets.- Chapter 24. Visual perception and observer performance.- Chapter 25. Physiological and functional interpretation of image data.- Chapter 26. Clinical evaluations of new technologies.- Chapter 27. Image data management (storage, retrieval, transmission).- Chapter 28. Medical informatics.- Chapter 29. Imaging for precision medicine.- Chapter 30. Deep learning applied in Medical Imaging.- Index.