Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis /

Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep...

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Main Authors: Dey, Nilanjan, 1984-, editor 611303, ScienceDirect (Online service) 7722
Format: software, multimedia
Language:eng
Published: San Diego : Academic Press, 2019
Subjects:
Online Access:https://www.sciencedirect.com/science/book/9780128180044
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author Dey, Nilanjan, 1984-, editor 611303
ScienceDirect (Online service) 7722
author_facet Dey, Nilanjan, 1984-, editor 611303
ScienceDirect (Online service) 7722
author_sort Dey, Nilanjan, 1984-, editor 611303
collection OCEAN
description Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images.
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institution Universiti Teknologi Malaysia - OCEAN
language eng
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publishDate 2019
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spelling KOHA-OAI-TEST:6064392023-11-15T13:15:49ZClassification Techniques for Medical Image Analysis and Computer Aided Diagnosis / Dey, Nilanjan, 1984-, editor 611303 ScienceDirect (Online service) 7722 software, multimedia Electronic books 631902 San Diego : Academic Press,©20192019engClassification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images.Chapter 1. Classification of unhealthy and healthy neonates in neonatal intensive care units using medical thermography processing and artificial neural network -- Chapter 2. Use of health-related indices and classification methods in medical data -- Chapter 3. Image analysis for diagnosis and early detection of hepatoprotective activity -- Chapter 4. Characterization of stuttering dysfluencies using distinctive prosodic and source features -- Chapter 5. A deep learning approach for patch-based disease diagnosis from microscopic images -- Chapter 6. A breast tissue characterization framework using PCA and weighted score fusion of neural network classifiers -- Chapter 7. Automated arrhythmia classification for monitoring cardiac patients using machine learning techniques -- Chapter 8. IOT-based fluid and heartbeat monitoring for advanced healthcare -- Index.Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images.Diagnostic imagingImaging systems in medicinehttps://www.sciencedirect.com/science/book/9780128180044URN:ISBN:9780128180044Remote access restricted to users with a valid UTM ID via VPN.
spellingShingle Diagnostic imaging
Imaging systems in medicine
Dey, Nilanjan, 1984-, editor 611303
ScienceDirect (Online service) 7722
Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis /
title Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis /
title_full Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis /
title_fullStr Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis /
title_full_unstemmed Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis /
title_short Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis /
title_sort classification techniques for medical image analysis and computer aided diagnosis
topic Diagnostic imaging
Imaging systems in medicine
url https://www.sciencedirect.com/science/book/9780128180044
work_keys_str_mv AT deynilanjan1984editor611303 classificationtechniquesformedicalimageanalysisandcomputeraideddiagnosis
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