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1、Proceedingsofthe5thInternationalConferenceonInformationTechnologyandApplicationinBiomedicine,inconjunctionwithThe2ndInternationalSymposium&SummerSchoolonBiomedicalandHealthEngineeringShenzhen,China,May30-31,2008ImplementationofMedicalImageSegmentationinCUDA11*2*LeiPan,LixuGu,Jian
2、rongXu1Schoolofsoftware,ShanghaiJiaotongUniversity,P.R.China,2ShanghaiRenjiHospital,Shanghai,P.R.ChinapurposeGPUarea.NVIDIA®CUDA™technologyisaAbstract—AsthefastdevelopmentofGPU,peopletendtouseitformoregeneralpurposesthanitsoriginalgraphicfundamentallynewcomputingarchitecturethate
3、nablestherelatedwork.ThehighparallelcomputationcapabilitiesofGPUtosolvecomplexcomputationalproblemsinconsumer,GPUarewelcomedbyprogrammerswhoworkatmedicalbusiness,andtechnicalapplications.CUDA(ComputeimageprocessingwhichalwayshavetodealwithalargescaleofUnifiedDeviceArchitecture)te
4、chnologygivesvoxelcomputation.ThebirthofNVIDIA®CUDA™technologycomputationallyintensiveapplicationsaccesstotheandCUDA-enabledGPUsbroughtarevolutioninthegeneraltremendousprocessingpowerofNVIDIAgraphicspurposeGPUarea.Inthispaper,weproposetheprocessingunits(GPUs)througharevolutionary
5、newimplementationofseveralmedicalimagesegmentationalgorithmsusingCUDAandCUDA-enabledGPUs,compareprogramminginterface.CUDAalsoprovidesordersoftheirperformanceandresultstothepreviousimplementationinmagnitudemoreperformanceandsimplifiessoftwareoldversionofGPUandCPU,indicatetheadvant
6、agesofusingdevelopmentbyusingthestandardClanguage[4].CUDAtechnologyandhowtodesignalgorithmtomakefulluseSegmentationisafundamentalprobleminthemedicalofit.imageanalysis.Thegeneralsegmentationproblemistheprocessofpartitioninganimageordata-setintoanumberofKeywords—CUDA,GPU,Segmentati
7、on,RegionGrowing,homogeneoussegments[5].AlthoughthemethodsofimageWatershedsegmentationhavebeenimprovedsignificantlyrecently,itisstillaverydifficultprobleminpractice[6].I.INTRODUCTIONInthispaper,CUDAtechnologyisemployedtoimplementComparedtoCPU,GPUhasmorepowerfulperformancedifferen
8、tsegmentationalgorithmsoverrealmedicalim
