光学相干断层影像（OCT）是一种应用于血管的影像新技术，其高分辨率和可量化分析等特点，使其能够检测血管内膜和斑块表面的特殊结构并发现微小病变。特别是随着其在识别冠状动脉粥样硬化斑块、优化经皮冠状动脉介入（PCI）治疗、辅助医生制定相关诊断和治疗策略以及支架术后评估等方面的应用相继展开，OCT 已经成为心血管疾病诊断的有效工具。本文提出了一种基于先验边界条件的冠脉 OCT 内膜轮廓序列提取算法，在 Chan-Vese 模型基础上通过改进演化权函数把轮廓曲线的局部信息引入模型，控制曲线边界演化速度，并在模型中加入梯度能量项和基于先验边界条件的内膜轮廓形状限制项，进一步约束曲线演化轮廓的形状，最终实现冠脉血管内膜轮廓的序列提取。与作为金标准的专业医生手动分割结果进行实验对比，结果表明本算法在冠脉 OCT 内膜轮廓模糊、失真、有导丝阴影及有斑块干扰等情况下均能准确提取冠脉血管内膜轮廓，提示本研究成果或可应用于临床辅助诊断和精确诊疗之中
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