基于血管内超声图像序列的相角配准与边缘检测

血管内超声成像可以显示血管内腔、管壁清楚的实时截面图像。实际采集的冠状动脉序列图像由于受脉动的影响而产生较大的重叠和错位,破坏毗邻图像的相关性,从而影响血管边缘检测、定量测量和3维重建的准确性。为进行精确的配准和边缘检测,采用一种新型的无需硬件设施的相角配准技术,经对序列图像的重采样得到相同相位下的连续图像,再基于快速主动轮廓算法模型提出一种适合血管内超声图像的自动边缘检测方法对重采样后的图像进行边缘检测。检测结果表明自动检测的内腔、血管面积与手动追踪非常吻合,具有较高的相关系数和较小的系统误差,可作为医生可靠而准确的诊断工具。

Automated Phasic Registration and Border Detection for Intravascular Ultrasound Image Sequences

Intravascular ultrasound(IVUS) can provide clear real-time cross-sectional images with lumen and plaque. Affected by pulse, the collected sequential images of the coronary artery, will be overlapped and distorted. As a result, the relativity between image sequences is destroyed. And the veracity of border detection of quantificational measurements and of reconstruction can not be achieved. In this paper, a new phasic registration technique without hard ware is used to resample the sequential images at the same phase. Then those resampled images are traced by a improved border detection technique based on fast active contour model. The experimental result shows significant accordance between the automatically detected luminal and vessel areas and the manual tracings with high correlation coefficients and small system error and the method can be a reliable and accurately way of diagnostis.