一种改进的自适应形变模型及其血管内超声图像边缘提取应用

An Improved Topologically Adaptable Snakes and the Applications in Edge Detection of IVUS Images

血管内超声(IVUS)图像冠状动脉血管壁内膜的边缘提取对冠状动脉疾病的诊断和治疗有着重要意义。提出一种改进的自适应形变模型(T-Snake),该模型能够解决基本T-Snake模型中的自交(Self-collisions)问题,并有着更高的数值计算精度。同时,基于改进的T-Snake模型,给出一种用于自动提取IVUS序列图像冠状动脉血管壁内膜边缘的方法。实验结果表明,所提出方法准确性和可靠性较高,对IVUS序列图像处理的可重复性和鲁棒性较好;表明了改进T-Snake模型的有效性和可实现性。

The edge detection of intravascular ultrasound （IVUS） images is important in the diagnosis and treatment of the coronary artery disease. An improved topologically adaptable snakes （T-Snake） was proposed in the paper, which could avoid the self-collisions of the T-Snake and had the advantage of higher numerical precision. A method based on the improved T-Snake to automatically detect the intima edge of IVUS image was also proposed. Experiments showed that the method was accurate, reproducible and robust for sequential IVUS frames. The improved T-Snake was effective and realizable as well.