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机构地区:[1]清华大学计算机科学与技术系,北京100084 [2]北京安贞医院心内科,北京100029
出 处:《光学精密工程》2013年第9期2381-2387,共7页Optics and Precision Engineering
基 金:国家自然科学基金资助项目(No.60971006);国家高技术研究发展计划(863计划)资助项目(No.2013AA013702)
摘 要:研究了冠脉光学相干层析(OCT)图像血管壁内轮廓的自动提取方法以提高算法的鲁棒性和计算效率。首先,利用冠脉OCT体数据中相邻图像之间的相关性去除鞘管信号对边缘提取的影响。接着,采用射线发射法估计血管中心,并以血管中心作为极点对去除鞘管信号的图像进行极坐标变换。然后,采用分块阈值滤波去除变换后图像的噪声并提取上边缘。最后,做逆极坐标变换得到血管壁的内轮廓。对400多幅测试图像的实验结果表明,该方法可以正确提取冠脉OCT图像的血管壁内轮廓,每幅图像的平均处理时间约为1.2 s。该方法不仅能够正确处理血管分叉或鞘管干扰大的图像,而且计算效率高,因此在鲁棒性和处理速度上具有优势。An automatic extracting method for the image of irmer contour of a vessel wall from intra- coronary Optical Coherence Tomography (OCT) was investigated to improve the robustness and com- puting efficiency of traditional algorithms. Firstly, the correlation between OCT images in volume da- ta was used to remove the effect of the signal caused by a catheter on the edge extraction. Then, the ray shooting method was taken to estimate the center of vessel, and the center was chosen as the pole to do a polar transform on the OCT image. Furthermore, the transformed image was partitioned into several parts, these parts were denoised separately by different thresholds and the upper edge was ex- tracted from the denoised image. Finally, the inner contour of the vessel wall was obtained by an in- verse polar transform. Experimental results on more than 400 images indicate that the inner contours of vessel walls of intracoronary OCT images can be detected accurately, and the average processing time for each image is about 1.2 s. In conclusion, the method can deal with OCT images with vascularbifurcation and ones influenced by catheter largely at higher speeds, so it has advantages in robustness and computational efficiency.
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