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Publicado por Taylor & Francis Ltd, London, 2024
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Añadir al carritoPaperback. Condición: new. Paperback. 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 This book focuses on implementation of a possible Hybrid Image Examination technique for medical images describing various image thresholding and segmentation methods along with essential details, such as test image preparation, implementation of a chosen thresholding operation, evaluation of threshold image, supported by pertinent case studies. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Añadir al carritoPaperback. Condición: new. Paperback. 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 This book focuses on implementation of a possible Hybrid Image Examination technique for medical images describing various image thresholding and segmentation methods along with essential details, such as test image preparation, implementation of a chosen thresholding operation, evaluation of threshold image, supported by pertinent case studies. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Publicado por Taylor & Francis Ltd, London, 2024
ISBN 10: 0367534991 ISBN 13: 9780367534998
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Añadir al carritoPaperback. Condición: new. Paperback. 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 This book focuses on implementation of a possible Hybrid Image Examination technique for medical images describing various image thresholding and segmentation methods along with essential details, such as test image preparation, implementation of a chosen thresholding operation, evaluation of threshold image, supported by pertinent case studies. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Añadir al carritoTaschenbuch. Condición: Neu. Hybrid Image Processing Methods for Medical Image Examination | Venkatesan Rajinikanth (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | CRC Press | EAN 9780367534998 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book focuses on implementation of a possible Hybrid Image Examination technique for medical images describing various image thresholding and segmentation methods along with essential details, such as test image preparation, implementation of a chosen thresholding operation, evaluation of threshold image, supported by pertinent case studies.