外文资料-- Glioma Tissue Modeling by Combing the Information of MRI and in vivo Multivoxel MRS.PDF外文资料-- Glioma Tissue Modeling by Combing the Information of MRI and in vivo Multivoxel MRS.PDF

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GLIOMATISSUEMODELINGBYCOMBINGTHEINFORMATIONOFMRIANDINVIVOMULTIVOXELMRSWEIBEIDOU,AOYANDONG,PINGCHITSINGHUANATIONALLABORATORYFORINFORMATIONSCIENCEANDTECHNOLOGYDEPTOFELECTRONICENGINEERING,TSINGHUAUNIVERSITY,BEIJING,100084,PRCHINAEMAILDOUWBTSINGHUAEDUCNSHAOWULINEUROIMAGINGCENTEROFTIANTANHOSPITALCAPITALMEDICALUNIVERSITY,BEIJING,PRCHINAJEANMARCCONSTANSUNITD’IRM,EA3916,CHRUCAEN,FRANCEABSTRACTTHISPAPERPRESENTSAGLIOMAMODELIZATIONMETHODANDAREGRESSIONLIKEMODELTOCREATEAGRADUALLYGLIOMAIMAGEGLIOIMMULTIMODALSIGNAL,IMAGESOFMAGNETICRESONANCEIMAGINGMRIANDINVIVOMULTIVOXELMRSPECTROSCOPYMRSARECOMBINEDBYTHEREGRESSIONLIKEMODELWITHSPATIALRESOLUTIONREGISTRATIONTHISMODELINGMETHODCONSISTSOFFEATUREMODELSOFGLIOMASUCHASTHESIGNALINTENSITYOFMRIMAGEANDTHEMETABOLITECHANGESOFMRS,THECORRELATIONMODELNOTEDASMETABOLITESRATIOMETARANDTHECOMBINEDREGRESSIONLIKEMODELTHEESTIMATEDGLIOIMINCLUDESBOTHBRAINSTRUCTUREANDGLIOMAGRADEINFORMATIONANONLINEARMODELISPROPOSEDANDVALIDATEDINTHISPAPERTHETESTINGDATAISACQUIREDBYSIEMENSTRIOTIM3TANDSYNGOMRB15ATBEIJINGTIANTANHOSPITALOFCHINATHEMRSOFTHREEGLIOMAPATIENTS,TWOAFFECTEDBYASTROCYTOMAANDONEBYGLIOMA,ANDTHECHEMICALSHIFTIMAGINGCSIREFERENCET2IMAGESWERECONSIDEREDINOURVALIDATIONEXPERIMENTTHERESULTINGGLIOIMSARECOMPAREDWITHGROUNDTRUTHPROVIDEDBYNEURORADIOLOGISTSOFTIANTANANDVERIFIEDWITHTHEIRPATHOLOGYREPORTTHEYREPORTTHATOURMETHODANDMODELAREVERYEFFICIENTKEYWORDSMRSPECTROSCOPY;BRAIN;GLIOMA;CHEMICALSHIFTIMAGING;MRI;IMAGE;MODELING;COMBINATIONIINTRODUCTIONTODIAGNOSEBRAINTISSUEABNORMALITIES,LIKETUMOR,IT’SNECESSARYTOUSEMULTISPECTRALMAGNETICRESONANCEIMAGESMRIS,SUCHAST1WEIGHT,T2WEIGHT,GADOLINIUM,FLAIRETCINORDERTOFINDSOMEOFTUMOR’SPROPERTIESSUCHASSIZE,POSITION,SORT,ANDRELATIONSHIPWITHOTHERTISSUES,ETCBUTTHETUMORTYPEANDGRADEAREUSUALLYDIAGNOSEDFROMHISTOPATHOLOGICALEXAMINATIONOFASURGICALSPECIMENHOWEVER,HYDROGEN11HMAGNETICRESONANCESPECTROSCOPYMRSISANONINVASIVEMRTECHNIQUETHATPROVIDESBIOCHEMICALINFORMATIONOFMETABOLITESTHEMAJORBIOCHEMICALCHARACTERISTICSCANNONINVASIVELYPROVIDEUSEFULINFORMATIONONBRAINTUMORTYPEANDGRADE1INMANYSTUDIES,INVIVO1HMRSHASBEENPRESENTEDFORDETERMININGTHETYPEANDGRADEOFTUMORS123SINCEINVIVOMRSMEASUREMENTSANDANALYSISAREDEPENDENTONTHEACQUISITIONTECHNICALTHATCOMPROMISETHESPATIALRESOLUTIONANDACCURACYFORRESULTINGMETABOLITEVALUES4,METABOLICCHANGESWITHDISEASEISFREQUENTLYSUBTLEANDDIFFUSEFURTHERMORE,BYCHEMICALSHIFTIMAGINGCSITECHNIQUE,THEMETABOLITEIMAGESSOCALLEDMRSPECTROSCOPICIMAGINGMRSICANBECREATEDBYMULTIVOXELMRSINFORMATION,BUTITISNOTVISUALLYINTERPRETABLEINTHESENSEOFASTRUCTURALMRI4SOTHAT,FORTHETUMORTISSUECLASSIFICATION,ITISIMPORTANTTHATMRSIISCOMBINEDWITHMRITOESTIMATETHEVARIATIONOFMETABOLITESANDTOYIELDMUCHINFORMATIONREGARDINGTISSUEDURINGMORETHANADECADE,AUTOMATICBRAINTUMORCLASSIFICATIONBYMRSHASBEENDEVELOPED5,BUTTHEMORECLEARDEFINITIONOFBRAINTUMORTYPEANDGRADEMAYBEOBTAINEDBYCOMBINATIONOFMRSIANDMRI5ATECHNIQUETODIFFERENTIATEGLIOBLASTOMAFROMMETASTASISLESIONSBYUSINGMRIANDMRSDATAHASBEENPUBLISHEDIN6WANGETALDESCRIBEDACLASSIFICATIONOFBRAINTUMORSBYUSINGFEATURESSELECTIONANDFUZZYCONNECTEDNESSIN7,THESEFEATURESAREEXTRACTEDFROMMRIANDMRSDATATHEREARETWODIFFICULTIESFORCOMBINGMRSIDATAANDMRIDATAFIRSTLY,THESEDATAAREFROMDIFFERENTMODALITIES,SOTHEYARENOTINTHESAMESPATIALRESOLUTION,VERYLOWSPATIALRESOLUTIONINVOXELFORMRSIANDHIGHSPATIALRESOLUTIONINPIXELFORMRISECONDLY,ONEMRIMAGECORRESPONDSTOTHEDISTRIBUTIONOFALLTISSUES,ORTISSUESTRUCTUREBUTONEMRSIMAGEISAPROJECTIONIMAGEWHICHCORRESPONDSTOONEMETABOLITEORRATIOBETWEENSEVERALMETABOLITESSOTHEDIFFERENTMETABOLITEVALUESMAKEVARIATIONMRSIMAGES,JUSTLIKETHEMAPPINGOFMETABOLITEDISTRIBUTIONSBYMRSIPRESENTEDIN8THEQUESTIONFORAPPLICATIONISHOWTOCOMBINETHESEMRSIMAGESANDMRIMAGESTOGIVEANAUTOMATICTISSUECLASSIFICATIONRESULTTHEKEYPOINTOFTHECOMBINATIONISHOWTOMODELTHEMETABOLITEDISTRIBUTIONFROMMRS,WHICHCORRESPONDSTOINFORMATIONFROMMRIMAGESFORAUTOMATICDESCRIPTIONOFBRAINTUMORTYPEANDGRADE,WEPROPOSEAMODELIZATIONMETHODOFGLIOMATISSUESBYCOMBINGTHEINFORMATION,FROMMRIMAGESANDMULITIVOXELMRSDATAITCANCREATEAMRSWEIGHTEDMRIMAGEAUTOMATICALLYWHICHKEEPSTHEHIGHSPATIALRESOLUTIONLIKEMRIMAGEANDTHEGREYLEVELSCORRESPONDTOTHEDETERIORATIONOFBRAINTISSUESTHESECONDPARTOFTHISPAPERINTRODUCESTHEGLIOMATISSUEFEATURESBOTHINMRSVALUESANDINMRIMAGESTHECOMBINATIONMODELINGOFTHETWOTYPESOFINFORMATIONISPRESENTEDINTHETHIRDSECTIONANDITSVALIDATIONISSHOWNINTHEFOURTHSECTIONTHECONCLUSIONABOUTOURRESEARCHISGIVENATTHEENDOFTHISPAPERTHISWORKISFUNDEDBYTSINGHUANATIONALLABORATORYFORINFORMATIONSCIENCEANDTECHNOLOGY(TNLIST)CROSSDISCIPLINEFOUNDATION9781424447138/10/25002010IEEEIIFEATURESMODELOFGLIOMATISSUEFOLLOWINGTHERESEARCHOFDIAGNOSINGBRAINTUMORBYMRIMAGESANDMRS,WECANSUMMARIZETWOTYPESOFCHARACTERISTICSOFGLIOMA,ONEISTHESIGNALINTENSITYOFT1WEIGHTANDT2WEIGHTIMAGES,ANDTHEOTHERONEISTHECHEMICALSHIFTVALUESOFMETABOLITESPRESENTEDBYMRSDATAASIGNALINTENSITYCHARACTERISTICSOFMRIMAGESWEHAVEPROPOSEDSOMEFUZZYMODELINGMETHODSOFDIFFERENTTUMOROUSCEREBRALTISSUESONMRIMAGESBASEDONFUSIONOFTISSUEFEATURESIN91011TABLEIDESCRIBESTHECHARACTERISTICSOFBRAINTISSUESBYCREATINGAGRADUALITYOFSIGNALINTENSITYASAFUNCTIONOFDIFFERENTTISSUESANDSEQUENCESOFMRI10,W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编号:201311062134463283    类型:共享资源    大小:1.62MB    格式:PDF    上传时间:2013-11-06
  
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本文标题:外文资料-- Glioma Tissue Modeling by Combing the Information of MRI and in vivo Multivoxel MRS.PDF
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