拓撲自適應梯度向量流模型及在醫(yī)學圖像分割中的應用.pdf

1、青島大學碩士學位論文拓撲自適應梯度向量流模型及在醫(yī)學圖像分割中的應用姓名：宋平蓮申請學位級別：碩士專業(yè)：計算機軟件與理論指導教師：蔣靜潘振寬20050603TopologiCallyAdaptableGVFModelanditsApplicationInMedicalImageSegmentationAbstractTheincreasinglyimportantroleofmedicalimaginginthediagnosisand

2、treatmentofdiseasehasopenedanarrayofchallengingproblemscenteredon廿lecomputationofaccurategeometricmodelsofanatomicstructuresfrommedicalimagesApromisingapproachtotacklesuchproblemsistheuseofdeformablemodelsThesepowerfulmo

3、delshaveproventobeeffectiveinsegmentingvisualizing，matchingandtrackinganatomicstructuresbyexploitingconstraintsderivedfromtheimagedatatogetherwithaprioriknowledgeaboutthelocation，sizeandshapeofthesestructuresFurthermore，

4、deformablemodelssupporthighlyintuitiveinl[eractionmechanisms也atallowmedicalscientistsandpractitionerstobringtheirexpertisetobearontheimageinterpretationtaskThisthesisproposes，developsandappliesanewclassofdiscretedeformab

5、lemodelsforthesegmentationandanalysisofmedicaIimagesThisnewdeformablemodelsisembeddedanddefinedintermsofallAmneCellDecomposition(ACD)frameworkItCandealwithobjectswithcomplexgeometriesandtopologiesMultipleinstancesofthemo

6、delsCanbedynamicallycreatedordestroyedandCanseamlesslysplitormergetoadapttoobjecttopologyTopologicallyadaptableGVFmodelcombinedwithflnovelandoriginalreparameterizationalgorithmOriginalmodelsmaintainthetraditionalparametr

7、icphysics—basedformulationofdeformablemodels，allowingthemtoincorporateapriorianatomicknowledgeintheformofenergyandforcebasedconstraintsandprovideintuitiveinteractivecapabilitiesNo、：elalgorittmasignificantlyextendstheabil

8、itiesoftraditionaldeformablemodels，enablingtopologicalflexibilityamongotherfeaturesSotopologicallyadaptableGVFmodelcanbeusedtoextract，reconstructandanalyzeeventhemostcomplexbiologicalstructuresfrommedicalimagesWeproposet