颈动脉粥样硬化斑块超声智能诊断的研究进展

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ABSTRACTCarotidatherosclerotic plaques（CAP）have become a significant risk factor forcardiovascular and cerebrovasculardiseases，suchasischemicstroke.Earlyidentificationofplaqueriskiscrucialforstrokeprevention.Ulrasound playsan importantroleinthediagnosisofCPA，itnotonlyassesss plaquesizeand morphologybutalsoprovides hmodyamic characteristics，therebyevaluating plaque stabilityandvulnerability.However，theaccuracyoftraditional examinationmethods is oftenlimitedbyfactors，suchasoperator experienceandequipmentresolution.The introductionofAItechnology，particularly deeplearning algorithms，hasbecomeanimportantaproach toenhancing clinical diagnosticprecisionandeficiency.This articlefocusesontheaplicationofAIintheultrasounddiagnosisofCAPinrecentyears，discusses itsapplicationinautomatic plaqueimagesgmetation，lassifcatio，issuecomponentientifiation，andstabilityassessment，andprovdesandepth analysis of the advantages，disadvantages，and challenges faced by current inteligent ultrasound diagnosis of CAP.

KEY WORDSUltrasonography;Carotid atherosclerotic plaque;AI; Deep learning;Risk assessment

颈动脉粥样硬化斑块（carotidatheroscleroticplaque，CAP）是动脉粥样硬化的重要表现之一，其形成与缺血性脑卒中等心脑血管疾病的发生密切相关[1]。（剩余12945字）