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Image feature selection by a genetic algorithm: Application to classification of mass and normal breast tissue

dc.contributor.authorSahiner, Berkman
dc.contributor.authorChan, Heang‐ping
dc.contributor.authorWei, Datong
dc.contributor.authorPetrick, Nicholas
dc.contributor.authorHelvie, Mark A.
dc.contributor.authorAdler, Dorit D.
dc.contributor.authorGoodsitt, Mitchell M.
dc.date.accessioned2017-01-06T20:45:00Z
dc.date.available2017-01-06T20:45:00Z
dc.date.issued1996-10
dc.identifier.citationSahiner, Berkman; Chan, Heang‐ping ; Wei, Datong; Petrick, Nicholas; Helvie, Mark A.; Adler, Dorit D.; Goodsitt, Mitchell M. (1996). "Image feature selection by a genetic algorithm: Application to classification of mass and normal breast tissue." Medical Physics 23(10): 1671-1684.
dc.identifier.issn0094-2405
dc.identifier.issn2473-4209
dc.identifier.urihttps://hdl.handle.net/2027.42/134755
dc.publisherAmerican Association of Physicists in Medicine
dc.publisherWiley Periodicals, Inc.
dc.subject.otherMedical imaging
dc.subject.otherArtificial neural networks
dc.subject.otherMammography
dc.subject.otherPhysicists
dc.subject.otherTesting procedures
dc.subject.otherMammography
dc.subject.otherXâ RAY RADIOGRAPHY
dc.subject.otherMAMMARY GLANDS
dc.subject.otherALGORITHMS
dc.subject.otherIMAGE ANALYSIS
dc.subject.otherNEOPLASMS
dc.subject.otherMORPHOLOGY
dc.subject.otherACCURACY
dc.subject.otherSTATISTICS
dc.subject.otherDESIGN
dc.subject.other87.56.04
dc.titleImage feature selection by a genetic algorithm: Application to classification of mass and normal breast tissue
dc.typeArticleen_US
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelMedicine (General)
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.contributor.affiliationumThe University of Michigan, Department of Radiology, Ann Arbor, Michigan 48109â 0030
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/134755/1/mp7829.pdf
dc.identifier.doi10.1118/1.597829
dc.identifier.sourceMedical Physics
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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