Signal and image processing techniques for the development of intelligent healthcare systems / E. Priya, V. Rajinikanth, editors.
This book comprehensively reviews the various automated and semi-automated signal and image processing techniques, as well as deep-learning-based image analysis techniques, used in healthcare diagnostics. It highlights a range of data pre-processing methods used in signal processing for effective da...
Saved in:
| Other Authors: | , |
|---|---|
| Format: | Ebook |
| Language: | English |
| Published: |
Singapore :
Springer,
[2021]
|
| Subjects: | |
| Online Access: | Springer eBooks |
Table of Contents:
- Chapter 1. An Integrated Design of Fuzzy C-Means and NCA based Multi-Properties Features Reduction for Brain Tumor Recognition
- Chapter 2. Hybrid Image Processing based Examination of 2D Brain MRI Slices to Detect Brain Tumour/Stroke Section
- A Study
- Chapter 3. Edge Enhancing Coherence Diffusion Filter for Level Set Segmentation and Asymmetry Analysis using Curvelets in Breast Thermograms
- Chapter 4. Lung Cancer Diagnosis Based on Image Fusion and prediction using CT and PET image
- Chapter 5. Segmentation and Validation of Infrared Breast Images using Weighted Level Set and Phase Congruency Edge Map Framework
- Chapter 6. Analysis of Material Profile for Polymer Based Mechanical Microgripper for Thin Plate Holding
- Chapter 7. Design and Testing of Elbow Actuated Wearable Robotic Arm for Muscular Disorders
- Chapter 8. A Comprehensive Study of Image Fusion Techniques and Their Applications
- Chapter 9. Multilevel Mammogram Image Analysis for Identifying Outliers, Misclassification using Machine Learning
- Chapter 10. A Review on Automatic Detection of Retinal Lesions in Fundus Images for Diabetic Retinopathy
- Chapter 11. Medical Image Watermarking: A Review on Wavelet Based Methods
- Chapter 12. EEG Signal Extraction Analysis Techniques
- Chapter 13. Classification of sEMG Signal based Arm Action using Convolutional Neural Network
- Chapter 14. An Automated Approach for the Identification of TB Images Enhanced by Non-uniform Illumination Correction.