Computer-Aided Diagnosis (CAD) Tools and Applications for 3D Medical Imaging, Volume 136 in the Advances in Computers series, presents detailed coverage of innovations in computer hardware, software, theory, design, and applications. Chapters in this updated release include Introduction to Computer-aided diagnosis (CAD) tools and applications, Enhancement of three-dimensional medical images, Machine Learning Based Techniques for Computer Aided Diagnosis, AI-based image processing techniques for the automatic segmentation of human organs, Watermarking over medical images, Compressive Sensing for 3D Medical Image Compression, and more.
Additional chapters cover Image encryption of medical images, Image Registration for 3D Medical Images, Texture-based computations for processing volumetric dental image, Language Processing in the Brain :an fMRI Study, Research challenges and emerging futuristic evolution for 3D medical image processing, Software based medical image analysis, and Automated 3D Visualization and Volume Estimation of Hepatic Structures for Treatment Planning of Hepatocellular Carcinoma.
1. Chapter One: Introduction to computer-aided diagnosis (CAD) tools and applications - p. 1 2. Chapter Two: Enhancement of three-dimensional medical images - p. 81 3. Abstract - p. 72 4. 1 Introduction - p. 72 5. 2 Fundamentals of 3D medical imaging - p. 75 6. 3 Image enhancement techniques - p. 77 7. 4 Advanced filtering approaches - p. 109 8. 5 Machine learning in image enhancement - p. 125 9. 6 Clinical applications - p. 131 10. 7 Challenges and future directions - p. 135 11. 8 Conclusion - p. 139 12. References - p. 141 13. Chapter Three: Machine learning-based techniques for computer-aided diagnosis - p. 170 14. Chapter Four: AI-based image processing techniques for the automatic segmentation of human organs - p. 215 15. Chapter Five: Watermarking over medical images - p. 249 16. Chapter Six: Compressive sensing technique for 3D medical image compression - p. 305 17. Chapter Seven: Image encryption of medical images - p. 364 18. Chapter Eight: Image registration for 3D medical images - p. 407 19. Chapter Nine: Texture-based computations for processing volumetric dental image - p. 453 20. Chapter Ten: Language processing in the brain: An fMRI study - p. 493 21. Chapter Eleven: Research challenges and emerging futuristic evolution for 3D medical image processing - p. 565 22. Chapter Twelve: Software based medical/dental analysis - p. 653 23. Chapter Thirteen: Automated 3D visualization and volume estimation of hepatic structures for treatment planning of hepatocellular carcinoma - p. 722
Computer-Aided Diagnosis (CAD) Tools and Applications for 3D Medical Imaging, Volume 136 in the Advances in Computers series, presents detailed coverage of innovations in computer hardware, software, theory, design, and applications. Chapters in this updated release include Introduction to Computer-aided diagnosis (CAD) tools and applications, Enhancement of three-dimensional medical images, Machine Learning Based Techniques for Computer Aided Diagnosis, AI-based image processing techniques for the automatic segmentation of human organs, Watermarking over medical images, Compressive Sensing for 3D Medical Image Compression, and more.
Additional chapters cover Image encryption of medical images, Image Registration for 3D Medical Images, Texture-based computations for processing volumetric dental image, Language Processing in the Brain :an fMRI Study, Research challenges and emerging futuristic evolution for 3D medical image processing, Software based medical image analysis, and Automated 3D Visualization and Volume Estimation of Hepatic Structures for Treatment Planning of Hepatocellular Carcinoma.
1. Chapter One: Introduction to computer-aided diagnosis (CAD) tools and applications - p. 1 2. Chapter Two: Enhancement of three-dimensional medical images - p. 81 3. Abstract - p. 72 4. 1 Introduction - p. 72 5. 2 Fundamentals of 3D medical imaging - p. 75 6. 3 Image enhancement techniques - p. 77 7. 4 Advanced filtering approaches - p. 109 8. 5 Machine learning in image enhancement - p. 125 9. 6 Clinical applications - p. 131 10. 7 Challenges and future directions - p. 135 11. 8 Conclusion - p. 139 12. References - p. 141 13. Chapter Three: Machine learning-based techniques for computer-aided diagnosis - p. 170 14. Chapter Four: AI-based image processing techniques for the automatic segmentation of human organs - p. 215 15. Chapter Five: Watermarking over medical images - p. 249 16. Chapter Six: Compressive sensing technique for 3D medical image compression - p. 305 17. Chapter Seven: Image encryption of medical images - p. 364 18. Chapter Eight: Image registration for 3D medical images - p. 407 19. Chapter Nine: Texture-based computations for processing volumetric dental image - p. 453 20. Chapter Ten: Language processing in the brain: An fMRI study - p. 493 21. Chapter Eleven: Research challenges and emerging futuristic evolution for 3D medical image processing - p. 565 22. Chapter Twelve: Software based medical/dental analysis - p. 653 23. Chapter Thirteen: Automated 3D visualization and volume estimation of hepatic structures for treatment planning of hepatocellular carcinoma - p. 722
