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EE5359Project PatternRecognitionDiagnosticusingPhaseOnlyCorrelationtechniquesubmittedbyThejaswiniPurushotham1000616811 迈鼎 Fig 1Experimentalsetupformedicalimagediagnostics Whathasbeendonealready Afingerprintmatchingalgorithmusingphaseonlycorrelation 1 Theproposedtechniqueisparticularlyeffectiveforverifyinglow qualityfingerprintimagesthatcouldnotbeidentifiedcorrectlybyconventionaltechniques Applications Automateddetectionofosteoarthritisfromknee xray Microcalcificationclustersinmammograms EmphysemainCT alungpathologycharacterisedbydestructionoflung lungnoduledetectionfrompostero anteriorchestradiographs Cryo electronmicroscopy instructuralbiologyisoneofthefieldswhichrequiresfullyautomatedobjectdetectiontechniques SimulationResults Fig2 Correlationgraphfortwosimilarimageslengthofthepeak 1 Resultsforilluminationinvariance fig5 a and b aretheX rayimagesofthesamechestwithvariationinillumination fig6 Simulationresultfortheimagesinfig5 ApplicationofPOCforpulmonaryemphysemadetection Thereare80millionpatentswithdevelopedpulmonaryemphysemaallovertheworld3millionpatientsaredyingeveryyearStudieshaveshownthatlungtissueisaboutathirdofthelungvolumehastobedestructedbeforeemphysemacouldbedetected 11 Doctorshavetwomethodstodiagnosepulmonaryemphysema Oneofthemethodsisspirometry anotherisdiagnosticimaging Formerisaquantitativemethod however wecannotmakeanearlydetectionofthedisease TheclassicalmethodofCTimageobjectiveevaluationisthePI pixelindex method EmphysemashowsuponCTasareaswithlowattenuationcoefficients withabnormaldistribution Bydeterminingthenumberofpixelswithlowattenuation emphysemacanbedetected PIdeterminestheaveragenumberofpixelswithlowerattenuationthanthelimitvalue lim Fig 9 SubjectA normallung Theseimagesshowhomogeneousdistributionofairinthelung Thewhitedotsrepresentareaswithlowerattenuationvaluesthan950HU 930HU and910HU respectively Thecalculatedpercentagesare 3 5 and10 13 Fig 10 SubjectC severeemphysema Thereisanobviousdestructionofthelungparenchyma Pixelindexes 34 48 and62 13 IssueswithPImethod ThePImethodisagood well knownmeasureofemphysema Butitisnotabletodetectemphysemaincasesinwhichemphysemaandfibrosisoccuratthesametime Thisisbecausefibrosistendstoincreasetheattenuationco efficientofpixelswhereasemphysematendstoreducetheattenuationco efficientofpixels ToreducethehealthriskfromexposuretoradiationwhilemakingaCTscan itisdesirabletousearadiationdosethatisaslowaspossible However theconstraintonirradiationdoseleadstoconsiderablenoiseinCTscans RadiationdosagesdirectlyinfluencethePIindex Fig 11 Coronalsliceanditsaccompanyingemphysemamapcalculatedforathresholdof930HU a b Scanwithclinicalradiationdose PI 13 3 c d Approximatelycorrespondingsliceofascanofthesamepatientwithatentimeslowerradiationdose PI 15 8 Fig 12 1a 1b 1c Simulationresultsforemphysemadetection Fig 123 Simulationresultsforemphysemaprogression 4a istheimageofahealthyindividual 4b 4c and 4d areimagesoftheemphysemaindifferentprogressivestages 4e showsthatthere11 7 differencebetween 4a and 4b 4f showsthatthereis 58 differencebetween 4b and 4c 4g showsthatthereis 02 changebetween 4c and 4d POCmethodgivesadirectmappingbetweenthenumberofaffectedpixelsandthepercentageofvisiblepixelsonthePOCmap POCmethodscoresoverthetraditionalPImethodintermsoftheRadiationdosage PImethodgivesbetterperformanceathigherdosagesofradiation ButthePOCmethodisnotdependantonthebrightnessoftheimage HenceitisabettermethodcomparedtothePImethod Thistechniquecanbeextendedandverifiedoverotherpathologieslikeosteoarthritis LungNoduleDetectionandMicrocalcificationclustersinmammograms References 1 Fazl e Basit M Y JavedandU Qayyum FaceRecognitionUsingProcessedHistogramAndPhase OnlyCorrelation POC InternationalConferenceonEmergingTechnologies ICET2007 pp238 242 Nov 2007 2 C Nakajimaetal ObjectRecognitionAndDetectionByaCombinationOfSupportVectorMachineAndRotationInvariantPhaseOnlyCorrelation 15thInternationalConferenceonPatternRecognition IEEEProc Vol 4 pp787 790 Sept 2000 3 J Z Wangetal InvestigationOfAPhase OnlyCorrelationTechniqueForAnatomicalAlignmentOfPortalImagesInRadiationTherapy Phys Med Biol Vol 41 pp1045 1058 Jun 1996 4 H Nakajimaetal AFingerprintMatchingAlgorithmUsingPhaseOnlyCorrelation IEICETrans Fundamentals Vol 87 A pp682 691 Mar 2004 5 S Watanabe T TanakaandE Iwata BiometricAuthenticationUsingPhaseOnlyCorrelationWithCompensationAlgorithmForRotation SICE ICASE InternationalJointConference Vol 18 pp3711 3715 Oct 2006 6 G Yang X YU X Zhuanq CurrentStatusAndDevelopmentOfPatternRecognitionDiagnosticMethodsBasedOnMedicalImaging IEEEInternationalconferenceonNetworking SensingandControl Vol 10 pp567 572 Apr 2008 7 V ZarzosoandA K Nandi ComparisonBetweenBlindSeparationAndAdaptiveNoiseCancellationTechniquesForFetalElectrocardiogramExtraction inProc IEEColloquiumonMedialApplicationsofSignalProcessing Vol48 pp12 18 Oct 1999 8 Z Y Qianetal MedicalImagesEdgeDetectionBasedonMathematicalMorphology Proc OfIEEE EngineeinginMedicineandBiology27thAnnualConference pp6492 6495 Jan 2006 9 WHOFactsheetwebsite 10 R Kobayashietal AlgorithmofPulmonaryemphysemaanalysisusingcomparingwithexpiratoryandinspiratorystateofCTimages SICEAnnualConference2008 pp3105 3109 Aug 2008 11 R Uppaluri etal Quantificationofpulmonaryemphysemafromlungcomputedtomographyimages Respir Crit CareMed vol 156 pp 248 254 1997 12 Healthinformationwebsite 13 R A Blechschmidt R WerthschutzkyandU LOrcher AutomatedCTimageevaluationofthelung Amorphology basedconcept IEEEtransactionsonmedicalimaging 14 A Madani C Keyzer andP Gevenois Quantitativecomputedtomographyassessmentoflungstructureandfunctioninpulmonaryemphysema Eur Respir J vol 18 no 4 pp 720 730 2001 15 U Tyl n O Friman M Borga andJ E Angelhed Animprovedalgorithmforcomputerizeddetectionandquantificationofpulmonaryemphysemaathighresolutioncomputedtomography hrct Proc