Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montreal, Canada.
Montreal Heart Institute, Montreal, Canada.
Comput Med Imaging Graph. 2014 Mar;38(2):91-103. doi: 10.1016/j.compmedimag.2013.09.004. Epub 2013 Sep 19.
The goal of this study was to show the feasibility of a 2D segmentation fast-marching method (FMM) in the context of intravascular ultrasound (IVUS) imaging of coronary arteries. The original FMM speed function combines gradient-based contour information and region information, that is the gray level probability density functions of the vessel structures, that takes into account the variability in appearance of the tissues and the lumen in IVUS images acquired at 40 MHz. Experimental results on 38 in vivo IVUS sequences yielded mean point-to-point distances between detected vessel wall boundaries and manual validation contours below 0.11 mm, and Hausdorff distances below 0.33 mm, as evaluated on 3207 images. The proposed method proved to be robust in taking into account various artifacts in ultrasound images: partial shadowing due to calcium inclusions within the plaque, side branches adjacent to the main artery to segment, the presence of a stent, injection of contrast agent or dissection, as tested on 209 images presenting such artifacts.
本研究的目的是展示二维分割快速行进法（FMM）在冠状动脉血管内超声（IVUS）成像中的可行性。原始的 FMM 速度函数结合了基于梯度的轮廓信息和区域信息，即血管结构的灰度概率密度函数，考虑到在 40MHz 采集的 IVUS 图像中组织和管腔的外观变化。对 38 个体内 IVUS 序列的实验结果表明，在 3207 张图像上，检测到的血管壁边界和手动验证轮廓之间的平均点到点距离低于 0.11 毫米，Hausdorff 距离低于 0.33 毫米。该方法在考虑超声图像中的各种伪影时表现出很强的鲁棒性：由于斑块内钙成分引起的部分阴影、与主动脉相邻的侧支、支架的存在、造影剂的注射或夹层，在 209 张呈现这种伪影的图像上进行了测试。
