الفهرس 
MedicalImageAnalysisOnly 14 pages are availabe for public view
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Abstract
Recently,automatedanalysisofmedicalimagesbecomesimportantforeasierandfaster
clinical diagnosis.Identifyinghumanorgansisthekeycomponentforsuchanalysis,
i.e., segmentationoftheanatomicalstructuresfrommedicalimages.
Coronary arteriessegmentationinthree-dimensional(3D)imageshasgainedwide
interestinoldandrecentscientificresearchandisregardedasafundamentalstepin
evaluatingthedegreeofCoronaryArteryDisease(CAD)incardiacclinicaldiagnosis
and surgicalplanning.Thus,variousmethodshavebeendevelopedforsegmenting
coronaries fromdifferentcardiacimagingmodalities.
Previously developedsegmentationmethodsweredesignedinawaythatcanad-
dress thechallengingtaskofcoronaryarteries.Thechallengesofcoronarysegmentation
can besummarisedinfourpoints:thesmallsizeofcoronaries,structuresattachedto
coronaries hassimilarintensityandintensity,shapevariationsalongthevesselsand
presence ofcalcifications.
The researchproblemofcoronarysegmentationwasdividedintothreeparts.First,
enhancing the3Dinputimagesusingvesselenhancementtechniqueswhichmakeit
easier todetectandextractcoronaryvesselregionsinnextsteps.Second,recognizing
and segmentingcoronariesusingapropersegmentationmethodthatcanhandlethe
changesinintensityandgeometryalongcoronaries.Third,usingtheresultedcoronary
vesseltreefordetectingandquantifyingstenoses(narrowness).
A frameworkforacoronarysegmentation,stenosesdetectionandquantification
system isproposedalongwithacomprehensiveoverviewofthestate-of-artcoronary
segmentationalgorithms.
The proposedcoronarysegmentationframeworkwasdividedintothreemainparts:
enhancementandpreprocessing,coronarysegmentation,andstenosesdetectionand quantification.Inenhancement,inputCTAimagesareenhancedbyremovingcalci-
fications usingthresholding,makingcoronaryregionsmoreobvioususinghistogram
equalization andenhancingvesselregionsusingHessianbasedanalysis.Inputcenter-
lines arealsoresampledforbetteraccuracyofsegmentationresultsandsuchresampled
centerlinesareusedinavolumetricwrappingstep.Theresultedwrappedvolumeis
then usedinthesegmentationstepthatrecognizesandsegmentscoronaryvesselsusing
Otsu thresholdingtechnique.Finally,thesegmentedcoronariesarethenusedinafur-
ther steptodetectandquantifyvesselstenoses.Thiswasdonebyanalysingtheareaof
vesselcross-sectionsalongthewholecoronarytreetodetectstenosesandapplylinear
regression tothesecalculatedareastoquantifythedegreeof(stenoses)narrowing.
The proposedsystemwastestedandevaluatedon48ComputedTomographyAn-
giography(CTA)standarddatasetsofcoronarypatientsatdifferentlevelsofseverity.
The evaluationusesthreemetricsforcomparingobtainedsegmentationresultswith
the manualsegmentationannotatedbythreeexperiencedobservers.Stenosesdetec-
tion andquantificationresultsarealsoquantitativelyevaluatedusingtwoevaluation
metrics foreachstepbycomparingobtainedresultstodetectionandquantification
previously definedbyphysicians.Furthermoretheresultswerecomparedwithother
state-of-art algorithmsshowingthestrengthsandweaknessesoftheproposedsystem.