Automatic detection of inner contour of vessel wall from intracoronary optical coherence tomographic image

SHU Peng 1; SUN Yan-kui 1; SONG Xian-tao2

doi:10.3788/OPE.20132109.2381

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Automatic detection of inner contour of vessel wall from intracoronary optical coherence tomographic image

更新时间：2020-08-12

- Automatic detection of inner contour of vessel wall from intracoronary optical coherence tomographic image
- Optics and Precision Engineering Vol. 21, Issue 9, Pages: 2381-2387(2013)
- 作者机构：
  
  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
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20132109.2381
  CLC： Q-334;TP391.4
- Received：04 March 2013，
  
  Revised：25 April 2013，
  
  Published Online：30 September 2013，
  
  Published：15 September 2013
- 稿件说明：
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舒鹏孙延奎宋现涛. 由冠脉光学相干层析图像自动提取血管壁内轮廓[J]. 光学精密工程, 2013,21(9): 2381-2387

SHU Peng SUN Yan-kui SONG Xian-tao. Automatic detection of inner contour of vessel wall from intracoronary optical coherence tomographic image[J]. Editorial Office of Optics and Precision Engineering, 2013,21(9): 2381-2387
舒鹏孙延奎宋现涛. 由冠脉光学相干层析图像自动提取血管壁内轮廓[J]. 光学精密工程, 2013,21(9): 2381-2387 DOI： 10.3788/OPE.20132109.2381.

SHU Peng SUN Yan-kui SONG Xian-tao. Automatic detection of inner contour of vessel wall from intracoronary optical coherence tomographic image[J]. Editorial Office of Optics and Precision Engineering, 2013,21(9): 2381-2387 DOI： 10.3788/OPE.20132109.2381.

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。

Abstract

An automatic extracting method for the image of inner contour of a vessel wall from intracoronary Optical Coherence Tomography (OCT) was investigated to improve the robustness and computing efficiency of traditional algorithms. Firstly

the correlation between OCT images in volume data 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 extracted from the denoised image. Finally

the inner contour of the vessel wall was obtained by an inverse 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 vascular bifurcation and ones influenced by catheter largely at higher speeds

so it has advantages in robustness and computational efficiency.

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Keywords

references

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