000 03473cam a2200613Ii 4500
001 9781003082224
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006 m o d
007 cr |n|||||||||
008 201212t20212021flua ob 000 0 eng d
040 _aOCoLC-P
_beng
_erda
_cOCoLC-P
020 _a9781000300185
_qelectronic book
020 _a1000300188
_qelectronic book
020 _a9781000316568
_qelectronic book
020 _a1000316564
_qelectronic book
020 _a9781003082224
_qelectronic book
020 _a100308222X
_qelectronic book
020 _a9781000317220
_qelectronic book
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020 _a1000317226
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020 _z0367534967
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020 _z9780367534967
_qhardcover
035 _a(OCoLC)1226566196
035 _a(OCoLC-P)1226566196
050 4 _aRC78.7.D53
_bR35 2021eb
072 7 _aCOM
_x037000
_2bisacsh
072 7 _aTEC
_x007000
_2bisacsh
072 7 _aTEC
_x015000
_2bisacsh
072 7 _aMMP
_2bicssc
082 0 4 _a616.1
_223
100 1 _aRajinikanth, Venkatesan,
_eauthor.
_919551
245 1 0 _aHybrid image processing methods for medical image examination /
_cVenkatesan Rajinikanth, E. Priya, Hong Lin, and Fuhua Lin.
250 _aFirst edition.
264 1 _aBoca Raton, FL :
_bCRC Press,
_c2021.
264 4 _c©2021
300 _a1 online resource (xii, 183 pages)
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aIntelligent signal processing and data analysis
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
588 _aOCLC-licensed vendor bibliographic record.
650 0 _aDiagnostic imaging.
_96280
650 0 _aImage processing.
_97417
650 7 _aCOMPUTERS / Machine Theory
_2bisacsh
_919552
650 7 _aTECHNOLOGY / Electricity
_2bisacsh
_919553
650 7 _aTECHNOLOGY / Imaging Systems
_2bisacsh
_910809
700 1 _aPriya, E.,
_eauthor.
_919554
700 1 _aLin, Hong,
_eauthor.
_919555
700 1 _aLin, Fuhua,
_eauthor.
_919556
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9781003082224
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
942 _cEBK
999 _c72131
_d72131