Lightlab Imaging, Inc., Westford, MA, USA.
Phys Med Biol. 2011 Oct 21;56(20):6665-75. doi: 10.1088/0031-9155/56/20/010. Epub 2011 Sep 26.
To assist cardiologists investigating neointimal tissue growth on stents during follow-up with optical coherence tomography (OCT), we developed an automatic algorithm to locate deeply buried stent struts and to quantify the restenosis burden. The technique is based on an improved steerable filter for computing the local ridge strength and orientation. It also uses an ellipsoid fitting algorithm and continuity criteria to obtain globally optimal stent localization. The restenosis burden calculations were compared to manual assessment of OCT coronary artery image data obtained from in vivo human clinical studies. Compared to manual assessment by expert readers, the algorithm operated with > 97% accuracy in the measurement of mean and maximum restenosis burden. The results indicated that the technique yielded comparable accuracy in measuring restenosis burden, and significantly reduced user interaction time.
为了协助心脏病学家在光学相干断层扫描（OCT）随访中研究支架内新生内膜组织生长，我们开发了一种自动算法，用于定位深埋的支架支柱并定量评估再狭窄负担。该技术基于改进的可导向滤波器，用于计算局部脊强度和方向。它还使用椭圆拟合算法和连续性标准来获得全局最佳支架定位。将再狭窄负担的计算与从体内人体临床研究中获得的 OCT 冠状动脉图像数据的手动评估进行了比较。与专家读者的手动评估相比，该算法在测量平均和最大再狭窄负担方面的准确率超过 97%。结果表明，该技术在测量再狭窄负担方面具有相当的准确性，并显著减少了用户交互时间。
