简介:在乳房X线照片的Microcalcification簇是在乳房X线照片的microcalcifications的胸cancer.The改进的一个重要早符号是为簇microcalcifications.In的抽取的最重要的预处理技术之一这份报纸,我们在场为改进的一个新奇方法microcalcifications.Firstly,起始的microcalcification边被使用樱桃酒边操作员提取,并且discontinouse边被采用分数维的technique.Then连接,连续clo
简介:Anewwaveletvarianceanalysismethodbasedonwindowfunctionisproposedtoinvestigatethedynamicalfeaturesofelectroencephalogram(EEG).TheexprienmentalresultsshowthatthewaveletenergyofepilepticEEGsaremorediscretethannormalEEGs,andthevariationofwaveletvarianceisdifferentbetweenepilepticandnormalEEGswiththeincreaseoftime-windowwidth.Furthermore,itisfoundthatthewaveletsubbandentropy(WSE)oftheepilepticEEGsarelowerthanthenormalEEGs.
简介:Osteosarcomaisprimarymalignantneoplasmsderivedfromcellsofmesenchymalorigin,andoftenhasdistinctphenotypesatdifferentstages.Thelocationoftumorandreactionzonecanbeidentifiedbyanexpertinmagneticresonanceimaging(MRI),withMRIbeingoneofthechoicesforevaluatingtheextentofosteosarcoma.However,itisstillachallengetoautomaticallyextracttumorfromitssurroundingtissuesbecauseoftheirlowintensitydifferencesinMRI.WeinvestigatedanapproachbasedonZernikemomentandsupportvectormachine(SVM)forosteosarcomasegmentationinT1-weightedimage(TIWI).Firstly,thedifferentordermomentsaroundeachpixelarecalculatedinsmallwindows.Secondly,thegrayscaleandthemodulevaluesofdifferentordermomentsareusedasatexturefeaturevectorwhichisthenusedasthetrainingsetforSVM.Finally,anSVMclassifieristrainedbasedonthissetoffeaturestoidentifytheosteosarcoma,andthesegmentedtumortissueisrenderedin3Dbytheraycastingalgorithmbasedongraphicsprocessingunit(GPU).TheperformanceofthemethodisvalidatedonT1WI,showingthatthesegmentationmethodhasahighsimilarityindexwiththeexpert’smanualsegmentation.
简介:Basedondiscretewavelettransform,bothrelativewaveletenergy(RWE)andsegmentwaveletentropy(SWE)ofelectroencephalogram(EEG)aredefinedinthispaper.TheRWEprovidesquantitativelytheinformationabouttherelativeenergyassociatedwithdifferentfrequencybandspresentintheEEG.TheSWEcarriesinformationaboutthedegreeoforderordisorderassociatedwithdifferenttimesegmentofEEGevolution,whichcandeterminethetime-segmentlocalizationsofabnormaldynamicprocessesofbrainactivityduetothelocalizationcharacteristicsofthewavelettransform.TheexperimentalresultsshowthattheRWEandSWEaredifferentbetweenepilepticEEGsandnormalEEGs,whichdemonstratethattheRWEandtheSWEarehelpfultoanalyzethedynamicbehaviorofdifferentEEGs.
简介:这研究的目的是根据EEG信号的复杂性措施的值识别大脑的函数和状态。30件正常样品和30件耐心的样品的EEG信号是镇定的。为未加工的数据基于预处理,为复杂性措施的一个计算程序被编译,所有样品的复杂性措施是计算的。吝啬的值和控制组的复杂性措施的标准错误作为0.33和0.10,并且正常的组作为0.53和0.08。当信心度是0.05时,为控制组的复杂性措施的正常人口平均数的信心间隔是(0.2871,0.3652),并且(0.4944,0.5552)为正常的组。正常样品和耐心的样品能清楚地是的统计结果表演由措施的价值区分了。在临床的药,结果能是是引用评估函数或状态,诊断疾病,监视大脑的康复进步。
简介:Recentinterestinmobile-basedhealthcarehasdrivensignificantdemandsonresearchingnon-contactelectrodesforelectrocardiogram(ECG)measurement.Whiletheconductivegelachievestherequirementinmakingagoodcontactbetweentheelectrodesandskin,severalproblemsappear.Agel-free,non-contactelectrodebasedoncapacitivecouplingtheorywasprovidedinthispaper,whichwasintegratedontheprintcircuitboard(PCB).TheexperimentalresultsshowedthatclearECGsignalscouldbeacquiredinthelaboratoryconditionsbycouplingtheelectrodestothechestofpatientsthroughcottonbelts.
简介:Bioluminescenceimagingisakindofemergingdetectiontechnologyatcellular,molecularandgeneticlevel.Themostpopularbioluminescenceimagingmodelisdiffusionapproximation(DA).However,becauseoftheill-posednessoftheDA-basedinverseproblemandtheinstabilityofreconstructionalgorithms,thelocationaccuracyofthereconstructedsourcesislow.Radiativetransferequation(RTE),whichconsidersthedirectionofthephotonmigrationandtheeffectofabsorptionandscatteringintissues,canaccuratelyexpressthetransmissionofbioluminescentphotonsthroughthetissues.Inthispaper,westudiedthebioluminescenceimagingbasedontheRTE.2Dsimulationswereperformed,andquantitativeevaluationwasgivenbytheabsolutesourcepositionerror,therelativesourceareaerrorandtheminimumboundingbox.TheresultsoftheexperimentshowedthattheimagingqualitybasedonRTEwasbetterthanthatonebasedonDA.
简介:Toinvestigatetherelationshipbetweensurfaceelectromyographyandsubjectiveassessmentofmusclefatigue,20youngmalevolunteersparticipatedintheexperimentofpistolholdingandaiming.sEMGoftheanteriordeltoidwasrecordedduringtheentireprocess,whilefatigueassessments(Borgscale)werecollectedevery30s.Wedividedthesignalintoseveralpartsandthenoctavebandmethodwasusedtocalculatemeanenergyofeachpart,anequationwasderivedbasedontherelationshipbetweenthemeanenergyofsEMGandBorgscale.Theresultsshowedthatthedegreeoflocalmusclefatiguecouldbedescribedbyacubiccurve,andcouldbeusedtoevaluateandmonitormusclefatigue.
简介:InordertoexplorethecorrelationbetweentheadjacentsegmentsofalongtermEEG,animprovedprincipalcomponentanalysis(PCA)methodbasedonmutualinformationalgorithmisproposed.Aone-dimensionEEGtimeseriesisdividedequallyintomanysegments,sothateachsegmentcanberegardedasanindependentvariablesandmulti-segmentedEEGcanbeexpressedasadatamatrix.Then,wesubstitutemutualinformationmatrixforcovariancematrixinPCAandconducttherelevanceanalysisofsegmentedEEG.Theexperimentalresultsshowthatthecontributionrateoffirstprincipalcomponent(FPC)ofsegmentedEEGismorelargerthanothers,whichcaneffectivelyreflectthedifferenceofepilepticEEGandnormalEEGwiththechangeofsegmentnumber.Inaddition,theevolutionofFPCconducetoidentifythetime-segmentlocationsofabnormaldynamicprocessesofbrainactivities,theseconclusionsarehelpfulfortheclinicalanalysisofEEG.
简介:Pulmonaryvesselsextractionisachallengingtaskinclinicalmedicine.Manypulmonarydiseasesareaccompaniedbythechangesofvesseldiameters.Thevesselsandtheirbranches,whichexhibitmuchvariability,aremostimportantinperformingdiagnosisandplanningthefollow-uptherapies.Inthispaper,weproposeanefficientapproachtopulmonaryvesselsextractionbasedonthecurveevolution.Thisapproachmodelsthevesselsasmonotonicallymarchingfrontunderthespeedfieldintegratingboththeregionandtheedgeinformationwhereanewregionspeedfunctionisdesignedandintegratedwiththeedgebasedspeedfunction.Duetotheregionbasedspeedterm,thefrontcouldevenpropagateinsmallnarrowvesselbranches.Tofurtherimprovethesegmentationresults,amulti-initialfastmarchingalgorithmisdevelopedtofastimplementthenumericalsolution,whichmayavoidthemonotonicallymarchingfrontleakingoutoftheweakboundarytooearlierandalsoreducethecomputationalcost.ThevalidityofourapproachisdemonstratedbyCTpulmonaryvesselsextraction.Experimentsshowthatthesegmentationresultsbyourapproach,especiallyonthenarrowthinvesselbranchesextraction,aremoreprecisethanthatoftheexistingmethod.
简介:Inrecentyears,thevolumetricapproachof3Dreconstructionhasemergedasapowerfulclinicmethodforbiomedicalapplications.Thisapproachisbasedonavoxelrepresentedobjectwhichmaintainsmanydetailsofthesurfaceandtheinternalcon-structuresoftheoriginalbody.Becauseofahugeamountofdata,thevolumedatasettakesalargesizeofmemory,andahighprocessingspeedisrequiredinorderto
简介:LevelSetmethodsarerobustandefficientnumericaltoolsforresolvingcurveevolutioninimagesegmentation.ThispaperproposesanewimagesegmentationalgorithmbasedonMumford-Shahmodule.ThemethodisusedtoCTimagesandtheexperimentresultsdemonstrateitsefficiencyandveracity.
简介:PACScanbeappliedinthenetworkarchitectureofClient/Server(C/S)andBrowser/Server(B/S)incurrentapplicationofhospitalinformationsystem.PACSViewerofB/Smodelisrealizedbymeansofthebrowsercommonly,butwebbrowserdoesnotsupportDICOMstandard.Inthisarticle,howtouseJavaApplettorealizethedisplayandoperationsofDICOMimageswillbediscussed.ThelightweightmethodtoviewDICOMimagesisveryfitfortelemedicaltreatment,andthesituationsnotrequirestrongabilityinimageoperations。
简介:介绍进散开张肌图象(DTI)的Rician噪音能在追踪的张肌计算和纤维以后带严肃的影响。减少Rician噪音的效果,我们建议认为基于小浪的散开方法降噪多信道的打的散开加权(DW)图象。当保存质地和边时,介绍变光滑的策略,在小浪领域利用各向异性的非线性的散开,成功地移开噪音。为了评估份量上,在为介绍进DW图象,peak-to-peaksignal-to-noise比率(PSNR)和signal-to-mean的Rician噪音的财务的介绍方法的效率摆平错误比率(SMSE)度量标准被采用。基于合成、真实的数据,我们计算了明显的散开系数(模数转换器)并且追踪了纤维。我们做了在介绍模型,波浪收缩和调整非线性的散开变光滑方法之间的比较。所有实验结果证明份量上并且视觉上介绍过滤器的更好的表演。
简介:Objective:Neuronsinthecochlearnucleusshowdifferentresponsepatternstotheshorttonebursts.Becauseofthelimitationsofanimalexperiments,itishardtoexploretheprinciple.Therefore,usingamodeltosimulateCNneuronswillbeafeasibleway.Methods:Basedontheinitialmodelmentionedinthepreviousstudy,weproposedanimprovedCNmodelinMATLABR2012b.Results:Bymodifyingtheparametersofthemodelwefoundtheinterchangesamong"primary-like","chopper",and"onset"responsepatterns.Furthermore,wesimulatedthe"pauser"responsepatternbyaddinganextrainputinourmodel.Conclusion:TheresultsindicatethatthesynapticintegrationsandtheinputmodescangiverisetodifferentcharacteristicsofCNneurons,whicheventuallydeterminetheresponsepatternsofCNneurons.