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Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems/ edited by E. Priya, V. Rajinikanth.
other author:	Priya, E.
Description:	XIV, 283 p. 117 illus., 52 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Biomedical engineering. -
Online resource:	https://doi.org/10.1007/978-981-15-6141-2
ISBN:	9789811561412

Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems
Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems[electronic resource] /edited by E. Priya, V. Rajinikanth. - 1st ed. 2021. - XIV, 283 p. 117 illus., 52 illus. in color.online resource.

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.

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 data mining in remote healthcare, and discusses pre-processing using filter techniques, noise removal, and contrast-enhanced methods for improving image quality. The book discusses the status quo of artificial intelligence in medical applications, as well as its future. Further, it offers a glimpse of feature extraction methods for reducing dimensionality and extracting discriminatory information hidden in biomedical signals. Given its scope, the book is intended for academics, researchers and practitioners interested in the latest real-world technological innovations.

ISBN: 9789811561412

Standard No.: 10.1007/978-981-15-6141-2doiSubjects--Topical Terms:

588770
Biomedical engineering.

LC Class. No.: R856-R857

Dewey Class. No.: 610.28

Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems
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505 0 $a 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.
520 $a 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 data mining in remote healthcare, and discusses pre-processing using filter techniques, noise removal, and contrast-enhanced methods for improving image quality. The book discusses the status quo of artificial intelligence in medical applications, as well as its future. Further, it offers a glimpse of feature extraction methods for reducing dimensionality and extracting discriminatory information hidden in biomedical signals. Given its scope, the book is intended for academics, researchers and practitioners interested in the latest real-world technological innovations.
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