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SECTION I OVERVIEW 1. Computational techniques in biomedical image analysis: overview SECTION II IMAGE PREPROCESSING AND SEGMENTATION TECHNIQUES 2. Multimodal medical image fusion using deep learning 3. Medical image fusion framework for neuro brain analysis 4. Automated detection of intracranial hemorrhage in noncontrast head computed tomography 5. Segmentation techniques for the diagnosis of intervertebral disc diseases SECTION III MEDICAL IMAGE CLASSIFICATION AND ANALYSIS 6. Heartbeat sound classification using Melfrequency cepstral coefficients and deep convolutional neural network 7. Comparative analysis of classification techniques for brain magnetic resonance imaging images 8. Hybrid feature selection-based feature fusion for liver disease classification on ultrasound images SECTION IV BIOMEDICAL IMAGE COMPRESSION AND TRANSMISSION 9. Discrete cosine transform 10. Segmentation-based compression techniques for medical images 11. Systematic survey of compression algorithms in medical imaging SECTION V BIOMEDICAL IMAGE SECURITY 12. Multilevel medical image encryption for secure communication 13. A modified digital signature algorithm to improve the biomedical image integrity in cloud environment 14. Medical imaging security and forensics: a systematic literature review

"Advances in Computational Techniques for Biomedical Image Analysis: Methods and Applications focuses on post-acquisition challenges such as image enhancement, detection of edges and objects, analysis of shape, quantification of texture and sharpness, and pattern analysis. It discusses the archiving and transfer of images, presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing. It examines various feature detection and segmentation techniques, together with methods for computing a registration or normalization transformation"--