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Hybrid Image Processing Methods for Medical Image Examination
By: E Priya, Venkatesan Rajinikanth, Hong Lin, Fuhua Lin
Hardcover | 24 December 2020
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In view of better results expected from examination of medical datasets (images) with hybrid (integration of thresholding and segmentation) image processing methods, this work focuses on implementation of possible hybrid image examination techniques for medical images. It describes various image thresholding and segmentation methods which are essential for the development of such a hybrid processing tool. Further, this book presents the essential details, such as test image preparation, implementation of a chosen thresholding operation, evaluation of threshold image, and implementation of segmentation procedure and its evaluation, supported by pertinent case studies. Aimed at researchers/graduate students in the medical image processing domain, image processing, and computer engineering, this book:
- Provides broad background on various image thresholding and segmentation techniques
- Discusses information on various assessment metrics and the confusion matrix
- Proposes integration of the thresholding technique with the bio-inspired algorithms
- Explores case studies including MRI, CT, dermoscopy, and ultrasound images
- Includes separate chapters on machine learning and deep learning for medical image processing
ISBN: 9780367534967
ISBN-10: 0367534967
Series: Intelligent Signal Processing and Data Analysis
Published: 24th December 2020
Format: Hardcover
Language: English
Number of Pages: 202
Audience: General Adult
Publisher: Taylor & Francis Ltd
Country of Publication: GB
Dimensions (cm): 15.8 x 24.1 x 2.1
Weight (kg): 0.46
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You Can Find This Book In
This product is categorised by
- Non-FictionMedicineOther Branches of MedicineMedical Imaging
- Non-FictionComputing & I.T.Computer ScienceImage Processing
- Non-FictionEngineering & TechnologyElectronics & Communications EngineeringElectronics EngineeringAutomatic Control Engineering
- Non-FictionComputing & I.T.Computer ScienceArtificial Intelligence
- Non-FictionEngineering & TechnologyEnergy Technology & EngineeringElectrical Engineering
- Non-FictionEngineering & TechnologyEnvironmental Science
- Non-FictionMedicineNursing & Ancillary ServicesBiomedical Engineering