Computational Imaging and Analytics in Biomedical Engineering

✍ Scribed by T. R. Ganesh Babu, U. Saravanakumar, Balachandra Pattanaik

• Publisher: Apple Academic Press
• Year: 2024
• Tongue: English
• Leaves: 356
• Category: Library

✦ Synopsis

"Computational Imaging and Analytics in Biomedical Engineering: Algorithms and Applications focuses on mathematical and numerical methods for medical images and data. The book presents the various mathematical modeling techniques, numerical analysis, computing and computational techniques, and applications of machine learning for medical images and medical informatics. It also focuses on programming concepts using MATLAB and Phython for medical image and signal analytics. The volume demonstrates the use of various computational techniques and tools such as machine learning, deep neural networks, artificial intelligence and human-computer interaction, fusion methods for CT and pet images, etc. for diagnosis of brain disorders, cervical cancer, lung disease, melanoma, atrial fibrillation and other circulatory issues, dental images, diabetes, and other medical issues. Key features: Addresses the various common challenges related to biomedical image analysis Presents a variety of mathematical models for medical images Discusses applications of algorithms on medical images for various medical issuses Describes the development of intelligent computing machines such as embedded systems Explores the programming techniques using MATLAB and Phython for biomedical applications This book presents a plethora of uses of algorithms and applications in computational imaging and analytics for the medical/health field. It will serve as a resource on recent advances and trends in the field of computational imaging, where computation is playing a dominant role in imaging systems"--

✦ Table of Contents

Cover
Half Title
Title Page
Copyright Page
Series Page
About the Editors
Table of Contents
Contributors
Abbreviations
Preface
1. Statistical Analysis of Seizure Data to Support Clinical Proceedings
2. Spatial Preprocessing in Segmentation of Brain MRI Using T1 and T2 Images
3. Comparative Volume Analysis of Pediatric Brain with Adult Brain Using T1 MRI Images
4. Comparison of Region of Interest and Cortical Area Thickness of Seizure and Hemosiderin-Affected Brain Images
5. Design and Analysis of Classifier for Atrial Fibrillation and Deep Neural Networks with ECG
6. Design and Analysis of Efficient Short Time Fourier Transform Based Feature Extraction for Removing EOG Artifacts Using Deep Learning Regression
7. Machine Learning for Medical Images
8. Innovations in Artificial Intelligence and Human Computer Interaction in the Digital Era
9. Computer-Aided Automatic Detection and Diagnosis of Cervical Cancer by Using Feature Markers
10. A Study on Sentiment Analysis
11. Applications of Magnetic Resonance Imaging Techniques and its Advancements
12. A Hybrid Clustering Approach for Medical Image Segmentation
13. Approaches for Analyzing Dental Images with Medical Image Processing with Its Statistics
14. An Investigation on Diabetes Using Multilayer Perceptron
15. Dermoscopic Implementation and Classification on Melanoma Disease Using Gradient Boost Classifier
16. Image Processing and Deep Learning Techniques for Lung Disease Segmentation Using KNN Classifier
17. Design Detecting and Classifying Melanoma Skin Cancer Using CNN with K Means Clustering
18. Detection of Lung Cancer Using Fusion Methods for CT and PET Images
19. A Framework Promoting Position Trust Evaluation System in Cloud Environment
20. Efficient Machine Learning Techniques for Medical Images
Index