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多图谱方法在脑MR图像分割中的应用（英文）.docx

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多图谱方法在脑MR图像分割中的应用（英文） ApplicationofMulti-AtlasMethodsinBrainMRIImageSegmentation Introduction: Magneticresonanceimaging(MRI)isanon-invasiveimagingtechniquethathasbecomeavaluabletoolinneuroscienceresearchandclinicalpractice.Itprovidesdetailedinformationaboutthestructureandfunctionofthebrain.OneofthecriticaltasksinbrainMRIanalysisissegmentation,whichreferstotheprocessofdelineatingdifferentbrainstructuresorregionsofinterest(ROIs)fromtheimage.Accurateandreliablesegmentationiscrucialforvariousapplications,suchasbrainmorphometry,surgicalplanning,anddiseasedetection.However,manualsegmentationisatime-consumingandsubjectiveprocessthatmayintroduceintra-andinter-observervariability.Toovercometheselimitations,automatedandsemi-automatedsegmentationmethodshavebeendeveloped,amongwhichmulti-atlasmethodshavegainedsignificantattention. Multi-AtlasMethods: Multi-atlasmethodsaimtoimprovetheaccuracyandrobustnessofimagesegmentationbyleveraginganatomicalinformationfrommultipleatlasesortemplates.Anatlasreferstoapre-segmentedimageoralabeledtemplatethatrepresentsthetargetstructure.GivenanewbrainMRIimage,multi-atlasmethodsregistermultipleatlasestotheimageandthenfusethepropagatedlabelstoobtainthefinalsegmentationresult.Severalstepsareinvolvedinthemulti-atlassegmentationprocess:atlasselection,registration,labelfusion,andpost-processing. AtlasSelection: Thefirststepinamulti-atlasmethodistoselectasetofatlasesthataremostsimilartothesubjectimage.Differentatlasselectionstrategieshavebeenproposed,includingrandomselection,population-basedselection,ordeformableregistration-basedselection.Thegoalistochooseatlasesthatcoverawiderangeofanatomicalvariabilityandprovideaccuraterepresentationsofthetargetstructures. Registration: Afteratlasselection,theselectedatlasesareregisteredtothesubjectimage.Registrationistheprocessofaligningtheatlases'anatomicalinformationwiththeimageusingadeformabletransformation.Variousregistrationalgorithms,suchasaffineregistration,non-rigidregistration,ordiffeomorphism-basedregistrat