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抑郁症患者的脑部MRI图像分类算法研究的任务书.docx

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抑郁症患者的脑部MRI图像分类算法研究的任务书 Title:ResearchProposalforClassificationAlgorithmofMRIImagesinPatientswithDepression 1.Introduction Depressionisawidespreadmentaldisorderaffectingmillionsofindividualsworldwide.Itcansignificantlyimpairpersonal,social,andoccupationalfunctioning.Identifyingandtreatingdepressionearlyiscrucialforimprovingpatientoutcomes.Imagingtechniques,suchasMagneticResonanceImaging(MRI),haveemergedaspowerfultoolsforunderstandingtheneurobiologicalbasisofdepression.ThegoalofthisresearchproposalistodevelopaclassificationalgorithmforMRIimagesthatcanaccuratelydistinguishbetweenindividualswithdepressionandhealthycontrols. 2.Objectives TheprimaryobjectiveofthisresearchproposalistodevelopaclassificationalgorithmfordiagnosingdepressionusingMRIimages.Specifically,theresearchaimsto: a)CollectadatasetofMRIimagesfrompatientswithdepressionandhealthycontrols. b)AnalyzethecollectedMRIimagestoidentifyrelevantfeaturesthatdistinguishbetweenthetwogroups. c)TrainandtestvariousmachinelearningalgorithmstoclassifyMRIimagesintodepressedandnon-depressedgroups. d)Validatethedevelopedalgorithmthroughcross-validationandcompareitwithexistingapproaches. e)InvestigatetherelationshipbetweentheidentifiedMRIfeaturesandtheseverityofdepressionsymptoms. 3.Methodology a)DataCollection:Collaboratewithhealthcareinstitutionsandresearchcenterstorecruitacohortofindividualsdiagnosedwithdepressionandage-matchedhealthycontrols.ObtainconsentfromparticipantsandcollectMRIimagesfollowingstandardizedprotocols. b)ImagePreprocessing:PreprocessthecollectedMRIimagestoremovenoise,correctintensityvariations,andstandardizeimagesizeandorientation.Applyqualitycontrolmeasurestoensurethereliabilityofthedataset. c)FeatureExtraction:UtilizeimageprocessingtechniquesandneuroimagingtoolstoextractrelevantfeaturesfromthepreprocessedMRIimages.Thesefeaturesmayincludevoxel-basedmorphometry,corticalthickness,subcorticalvolume,andfunctionalconnectivitymeasures. d)AlgorithmDevelopment:Employvariousclassificationalgorithms,suchassupport