基于统计形状模型的肝脏图像分割算法分析-(5727)

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1、硕士学位论文价函数，通过学习而得的各参数可以更好的指导匹配过程的形状拟合。同时降低了分割过程中搜索函数的复杂度，提高了分割的速度。本文采用的基于统计形状模型的灰度模型通过区域特征从总体上识别肝脏组织，又在边缘信息上优化细节。实验结果表明该方法能够提高分割的精度和稳定性。关键字：统计形状模型，灰度外观模型，边缘特征，区域特征，学习的代价函数V硕士学位论文RESEARCHOFLIVERIMAGESEGMENTATIoNBASEDoNSTATISTICALSHAPEMODELSName：LiChunLiSupervisor：Prof．FengQian

2、jinABSTRACTMedicalimagesegmentationisthetechniquethatdividestheimageintodifferentregionswhichtheinter-regionshavedifferentcharacteristicsandtheintra-regionissimilar,orextractstheinterestedobjectsfromtheimage．Thesegmentationtakesanimportantroleinthefieldofmedicalimageprocessi

3、ngandanalyzing．HoweveLmedicalimagesegmentationisputmoreemphasisontheextractingspecialregions，suchasorgansorcancers．Asthesametime，thedifferentregionsorobjectsshouldbeidentitywitlltheanatomicalstructure．Basedonmedicalimagesegmentation，theimagecontentsCanbebeReranalyzed，whichwi

4、llassistdoctorstodiagnoseandmakethetreatmentplancorrectly．Uptonow,therearelotsofsegmentationmethodsforallkindsofpurposes，butnooneCangenerallyapplytodifferentmodesofimagesanddifferentorgans．Moreover,Thereareflnumberoffactorsthatcausecurrentsegmentationalgorithmsfailtosatisfyt

5、heneedofclinicalpractice，includingtheindividualdifferencesinthetissueanatomy；slowcalculatingspeedandinaccuracy；andpoorimagequalityaffectedbynoise，intensiveinhomogeneityandpartialvolumeeffect(PVE)etc．Inaddition，itisdifficulttodescribethepracticalproblemcompletelyusingmathemat

6、icalmodels；thedissimilarityofthesegmentationobjectives；imagedegradationandSOon．Thereisnosuchanalgorithmofsegmentationwhichiscompetentforallkindsoftheproblems．SoweonlycantakethegivenproblemsandthespecialrequiresintoaccounttodevelopdifferentABSTRACTalgorithms，andbalancebetween

7、theprecision，thespeedandtherobustness．Forthesereasons，themedicalimagesegmentationhasbeenanimportantfieldinmedicalimageprocessingandanalysis．Theliveristhelargestglandinthebody(approximately1500grams)whichisvitalorgan．Ithasawiderangeoffunctions，includingdetoxification，excretio

8、n，bloodstorage，proteinsynthesis，andproductionofbiochemicalsnecessaryfordige