Arias-Lorza Andrés M, Petersen Jens, van Engelen Arna, Selwaness Mariana, van der Lugt Aad, Niessen Wiro J, de Bruijne Marleen
IEEE Trans Med Imaging. 2016 Mar;35(3):901-11. doi: 10.1109/TMI.2015.2501751. Epub 2015 Nov 18.
We present a new three-dimensional coupled optimal surface graph-cut algorithm to segment the wall of the carotid artery bifurcation from Magnetic Resonance (MR) images. The method combines the search for both inner and outer borders into a single graph cut and uses cost functions that integrate information from multiple sequences. Our approach requires manual localization of only three seed points indicating the start and end points of the segmentation in the internal, external, and common carotid artery. We performed a quantitative validation using images of 57 carotid arteries. Dice overlap of 0.86 ± 0.06 for the complete vessel and 0.89 ± 0.05 for the lumen compared to manual annotation were obtained. Reproducibility tests were performed in 60 scans acquired with an interval of 15 ± 9 days, showing good agreement between baseline and follow-up segmentations with intraclass correlations of 0.96 and 0.74 for the lumen and complete vessel volumes respectively.
我们提出了一种新的三维耦合最优表面图割算法,用于从磁共振(MR)图像中分割颈动脉分叉处的血管壁。该方法将内外边界的搜索整合到一个单一的图割中,并使用融合多个序列信息的代价函数。我们的方法仅需手动定位三个种子点,以指示颈内动脉、颈外动脉和颈总动脉分割的起点和终点。我们使用57条颈动脉的图像进行了定量验证。与手动标注相比,完整血管的Dice重叠率为0.86±0.06,管腔的Dice重叠率为0.89±0.05。在间隔15±9天采集的60次扫描中进行了重复性测试,结果表明基线分割和随访分割之间具有良好的一致性,管腔和完整血管体积的组内相关性分别为0.96和0.74。