Skip to main content
Elsevier

Advances in Computational Techniques for Biomedical Image Analysis

Methods and Applications

  • 1st Edition - May 28, 2020
  • Latest edition
  • Editors: Deepika Koundal, Savita Gupta
  • Language: English

Advances in Computational Techniques for Biomedical Image Analysis: Methods and Applications focuses on post-acquisition challenges such as image enhancement, detection of edges… Read more

Data Mining & ML

Unlock the cutting edge

Up to 20% on trusted resources. Build expertise with data mining, ML methods.

Explore now

Description

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.

Key features

  • 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

Readership

Medical imaging researchers, graduate students, clinical researchers

Table of contents

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

Product details

  • Edition: 1
  • Latest edition
  • Published: May 28, 2020
  • Language: English

About the editors

DK

Deepika Koundal

Deepika Koundal currently serves as a Senior Researcher at the University of Eastern Finland, specializing in Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision & Image Processing, and Cyber-Physical Systems. She holds a Ph.D. in Computer Science and Engineering and has received several prestigious accolades, including the MSCA Seal of Excellence from the European Commission. In 2023 and 2024, she was recognized as a top 2% researcher by Stanford University. She has over 13 years of teaching and research experience, having served in various academic roles including at NIT Hamirpur, Chitkara University, and UIET Panjab University. She has earned multiple research excellence awards from UPES and has published numerous research articles, edited notable books, and holds several patents. Furthermore, she contributes as a guest and associate editor for leading journals, including those published by IEEE and Elsevier.
Affiliations and expertise
Researcher, University of Eastern Finland, Joensuu, Finland

SG

Savita Gupta

Prof. Savita Gupta (SG) is a Professor in the Department of Computer Science and Engineering, University Institute of Engineering and Technology (UIET), Panjab University. She has received her M.E degree from Thapar University and Ph.D. degree in Computer Science and Engineering from the Punjab Technical University, Jalandhar. She has been working in Panjab University for more than 11 years and is currently designated as Director, UIET, Panjab University. She is passionately performing her research activities in the field of Signal and Image Processing, Medical Image Analysis, Wavelets based Signal and Image processing, Artificial Intelligence and Cognitive neuroscience. Her contributions in the field of speckle noise reduction in Ultrasound images is widely acknowledged in the field of biomedical engineering. She has contributed more than 40 research papers in reputed journals and more than 30 conference articles are there to her credit. So far, 5 students have completed their Ph.D. and 9 students are currently pursuing Ph.D under her supervision. She has an h-index of 66 and i10 index of 481.
Affiliations and expertise
Director, University Institute of Engineering Technology, Panjab University, Chandigarh, India

View book on ScienceDirect

Read Advances in Computational Techniques for Biomedical Image Analysis on ScienceDirect