Computer-aided Design and Diagnosis Methods for Biomedical Applications
1st Edition
Published on 12. March 2025
Book
Paperback/Softback
368 pages
978-0-367-63884-9 (ISBN)
Description
Computer-aided design (CAD) plays a key role in improving biomedical systems for various applications. It also helps in the detection, identification, predication, analysis, and classification of diseases, in the management of chronic conditions, and in the delivery of health services. This book discusses the uses of CAD to solve real-world problems and challenges in biomedical systems with the help of appropriate case studies and research simulation results. Aiming to overcome the gap between CAD and biomedical science, it describes behaviors, concepts, fundamentals, principles, case studies, and future directions for research, including the automatic identification of related disorders using CAD.
Features:
Proposes CAD for the study of biomedical signals to understand physiology and to improve healthcare systems' ability to diagnose and identify health disorders.
Presents concepts of CAD for biomedical modalities in different disorders.
Discusses design and simulation examples, issues, and challenges.
Illustrates bio-potential signals and their appropriate use in studying different disorders.
Includes case studies, practical examples, and research directions.
Computer-Aided Design and Diagnosis Methods for Biometrical Applications is aimed at researchers, graduate students in biomedical engineering, image processing, biomedical technology, medical imaging, and health informatics.
Features:
Proposes CAD for the study of biomedical signals to understand physiology and to improve healthcare systems' ability to diagnose and identify health disorders.
Presents concepts of CAD for biomedical modalities in different disorders.
Discusses design and simulation examples, issues, and challenges.
Illustrates bio-potential signals and their appropriate use in studying different disorders.
Includes case studies, practical examples, and research directions.
Computer-Aided Design and Diagnosis Methods for Biometrical Applications is aimed at researchers, graduate students in biomedical engineering, image processing, biomedical technology, medical imaging, and health informatics.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Academic
Illustrations
77 s/w Tabellen, 4 s/w Photographien bzw. Rasterbilder, 101 s/w Zeichnungen, 105 s/w Abbildungen
77 Tables, black and white; 101 Line drawings, black and white; 4 Halftones, black and white; 105 Illustrations, black and white
Dimensions
Height: 234 mm
Width: 156 mm
Thickness: 21 mm
Weight
597 gr
ISBN-13
978-0-367-63884-9 (9780367638849)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Varun Bajaj | G. R. Sinha
Computer-aided Design and Diagnosis Methods for Biomedical Applications
Book
04/2021
1st Edition
CRC Press
€206.70
Shipment within 15-20 days
Varun Bajaj | G. R. Sinha
Computer-aided Design and Diagnosis Methods for Biomedical Applications
E-Book
04/2021
1st Edition
CRC Press
€64.49
Available for download
Varun Bajaj | G. R. Sinha
Computer-aided Design and Diagnosis Methods for Biomedical Applications
E-Book
04/2021
1st Edition
CRC Press
€64.49
Available for download
Persons
Content
Chapter 1 Electroencephalogram Signals Based Emotion Classification in Parkinson's Disease Using Recurrence Quantification Analysis and Non-Linear Classifiers
Chapter 2 Sleep Stage Classification Using DWT and Dispersion Entropy Applied on EEG Signals
Chapter 3 Detection of Epileptic Electroencephalogram Signals Employing Visibility Graph Motifs
Chapter 4 Effect of Various Standing Poses of Yoga on the Musculoskeletal System Using EMG
Chapter 5 Early Detection of Parkinson Disease and SWEDD Using SMOTE and Ensemble
Chapter 6 Computer-Aided Design and Diagnosis Method for Cancer Detection
Chapter 7 Automated COVID-19 Detection from CT Images Using Deep Learning
Chapter 8 Suspicious Region Diagnosis in the Brain: A Guide to Using Brain MRI Sequences
Chapter 9 Medical Image Classification Algorithm Based on Weight Initialization-Sliding Window Fusion Convolutional Neural Network
Chapter 10 Positioning the Healthcare Client in Diagnostics and the Validation of Care Intensity
Chapter 11 Computer-Aided Diagnosis (CAD) System for Determining Histological Grading of Astrocytoma Based on Ki67 Counting
Chapter 12 Improved Classification Techniques for the Diagnosis and Prognosis of Cancer
Chapter 13 Discovery of Thyroid Disease Using Different Ensemble Methods with Reduced Error Pruning Technique
Chapter 14 Reliable Diagnosis and Prognosis of COVID-19
Chapter 15 Computer-Aided Diagnosis Methods for Non-Invasive Imaging of Sub-Skin Lesions
Index
Chapter 2 Sleep Stage Classification Using DWT and Dispersion Entropy Applied on EEG Signals
Chapter 3 Detection of Epileptic Electroencephalogram Signals Employing Visibility Graph Motifs
Chapter 4 Effect of Various Standing Poses of Yoga on the Musculoskeletal System Using EMG
Chapter 5 Early Detection of Parkinson Disease and SWEDD Using SMOTE and Ensemble
Chapter 6 Computer-Aided Design and Diagnosis Method for Cancer Detection
Chapter 7 Automated COVID-19 Detection from CT Images Using Deep Learning
Chapter 8 Suspicious Region Diagnosis in the Brain: A Guide to Using Brain MRI Sequences
Chapter 9 Medical Image Classification Algorithm Based on Weight Initialization-Sliding Window Fusion Convolutional Neural Network
Chapter 10 Positioning the Healthcare Client in Diagnostics and the Validation of Care Intensity
Chapter 11 Computer-Aided Diagnosis (CAD) System for Determining Histological Grading of Astrocytoma Based on Ki67 Counting
Chapter 12 Improved Classification Techniques for the Diagnosis and Prognosis of Cancer
Chapter 13 Discovery of Thyroid Disease Using Different Ensemble Methods with Reduced Error Pruning Technique
Chapter 14 Reliable Diagnosis and Prognosis of COVID-19
Chapter 15 Computer-Aided Diagnosis Methods for Non-Invasive Imaging of Sub-Skin Lesions
Index