Advances in Computational Techniques for Biomedical Image Analysis

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.

Advances in Computational Techniques for Biomedical Image Analysis: Method and Applications is ideal for researchers and post graduate students developing systems and tools for health-care systems.

• Covers various challenges and common research issues related to biomedical image analysis
• Describes advanced computational approaches for biomedical image analysis
• Shows how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc.
• Explores a range of computational algorithms and techniques, such as neural networks, fuzzy sets, and evolutionary optimization
• Explores cloud based medical imaging together with medical imaging security and forensics

Medical imaging researchers, graduate students, clinical researchers

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