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1、Tensor-basedBrainSurfaceModelingandAnalysisMooK.Chung1,KeithJ.Worsley2,SteveRobbins2andAlanC.Evans21DepartmentofStatistics,DepartmentofBiostatisticsandMedicalInformaticsKeckLaboratoryforFunctionalBrainImagingandBehaviorUniversityofWisconsin-MadisonMadison,WI53706.USA2MontrealNeurolo
2、gicalInstitute,McGillUniversity,Canadamchung@stat.wisc.eduOctober31,2002AbstractcorrectingintensitynonuniformityorRFinhomogeneityar-tifacts.WehaveusednonparametricnonuniformintensityWepresentaunifiedcomputationalapproachtotensor-normalizationmethod(N3),whicheliminatesthedepen-basedmo
3、rphometryindetectingthebrainsurfaceshapedenceofthefieldestimateonanatomy[18].Thenextdifferencebetweentwoclinicalgroupsbasedonmagneticstepisthetissueclassificationintothreetypes:graymat-resonanceimages.Ourapproachisnovelinasensethatter,whitematterandcerebrospinalfluid(CSF).Anartifi-wecom
4、binedsurfacemodeling,surfacedatasmoothingcialneuralnetworkclassifier[16,26]oramixturemodelandstatisticalanalysisinacoherentunifiedmathemati-clusteranalysis[8]canbeusedtosegmentthetissuetypescalframework.Thecerebralcortexhasthetopologyofaautomatically.Afterthetissueclassification,thecor
5、tical2Dhighlyconvolutedsheet.Betweentwodifferentclinicalsurfaceisusuallygeneratedasasmoothtriangularmesh.groups,thelocalsurfaceareaandcurvatureofthecortexThemostwidelyusedmethodfortriangulatingthesurfacemaydiffer.Itishighlylikelythatsuchsurfaceshapediffer-isthemarchingcubesalgorithm
6、[13].Levelsetmethod[19]encesarenotuniformoverthewholecortex.Bycomput-ordeformablesurfacesmethod[7]arealsoavailable.Ininghowsuchsurfacemetricsdiffer,theregionsofthemostourstudy,wehaveusedtheanatomicsegmentationusingrapidstructuraldifferencescanbelocalized.Toincreaseproximities(ASP)me
7、thod[14],whichisavariantofthethesignaltonoiseratio,diffusionsmoothingbasedonthedeformablesurfacesmethod,togeneratecorticaltriangu-explicitestimationofLaplace-Beltramioperatorhasbeenlarmeshesthathasthetopologyofasphere.Brainsub-developedandappliedtothesurfacemetrics.Asanillus-structu
8、ressuchasthebrainst
