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| LDR | 08098cam a2200000 a | ||
| 001 | 0100529513▲ | ||
| 003 | OCoLC▲ | ||
| 005 | 20211105102623▲ | ||
| 007 | ta ▲ | ||
| 008 | 201212t20212021flua ob 001 0 eng c▲ | ||
| 019 | ▼a1235967671▲ | ||
| 020 | ▼z9781003082224 (ebk.)▲ | ||
| 020 | ▼a0367534967 (hbk.)▲ | ||
| 020 | ▼a9780367534967 (hbk.)▲ | ||
| 035 | ▼a(OCoLC)1226566196▼z(OCoLC)1235967671▲ | ||
| 040 | ▼aYDX▼beng▼cYDX▼dUKAHL▼dN$T▼dOCLCO▼dTYFRS▼dYDXIT▼dOCLCO▼dTYFRS▼dOCLCF▼d221016▲ | ||
| 050 | 4 | ▼aRC78.7.D53▼bR35 2021eb▲ | |
| 082 | 0 | 4 | ▼a616.075▼223▲ |
| 090 | ▼a616.075▼bR161h▲ | ||
| 100 | 1 | ▼aRajinikanth, Venkatesan.▲ | |
| 245 | 1 | 0 | ▼aHybrid image processing methods for medical image examination /▼cVenkatesan Rajinikanth, E. Priya, Hong Lin, and Fuhua Lin.▲ |
| 260 | ▼aBoca Raton, FL :▼bCRC Press,▼c2021.▲ | ||
| 300 | ▼axii, 183 p. :▼bill. ;▼c25 cm.▲ | ||
| 490 | 0 | ▼aIntelligent signal processing and data analysis▲ | |
| 504 | ▼aIncludes bibliographical references and index.▲ | ||
| 520 | ▼aIn 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.▲ | ||
| 650 | 0 | ▼aDiagnostic imaging.▲ | |
| 650 | 0 | ▼aImage processing.▲ | |
| 700 | 1 | ▼aPriya, E.▲ | |
| 700 | 1 | ▼aLin, Hong.▲ | |
| 700 | 1 | ▼aLin, Fuhua.▲ |
Hybrid image processing methods for medical image examination
자료유형
국외단행본
서명/책임사항
Hybrid image processing methods for medical image examination / Venkatesan Rajinikanth, E. Priya, Hong Lin, and Fuhua Lin.
발행사항
Boca Raton, FL : CRC Press , 2021.
형태사항
xii, 183 p. : ill. ; 25 cm.
서지주기
Includes bibliographical references and index.
요약주기
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
0367534967 (hbk.) 9780367534967 (hbk.)
청구기호
616.075 R161h
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