Vessel segmentation in 2-D optical coherence tomography images

被引：0

作者：

Liu, Li-chang ^{[1
]}

Lee, Jiann-der ^{[2
]}

Hsu, Yu-wei ^{[3
]}

Tseng, Scott ^{[4
]}

Tseng, Ellen ^{[5
]}

Tsai, Meng-tsan ^{[2
]}

机构：

[1] MaruTong Co Ltd, Taipei, Taiwan

[2] ChangGung Univ, Dept Elect Engn, Taoyuan, Taiwan

[3] Natl Chiao Tung Univ, Dept Elect Engn, Hsinchu, Taiwan

[4] Kaohsiung Med Ctr, Sch Med, Kao, Taiwan

[5] Natl Taiwan Univ, Sch Med, Taipei, Taiwan

来源：

2013 ICME INTERNATIONAL CONFERENCE ON COMPLEX MEDICAL ENGINEERING (CME) | 2013年

关键词：

Optical coherence tomography; OCT; texture segmentation; fuzzy-c-mean; vessel;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

This paper described a novel region segmentation method to avoid difficulties of the threshold process used in traditional segmentation methods in 2-D optical coherence tomography (OCT) images. The speckle effect and diffusion problems make traditional image processing methods such as Canny edge and Otsu methods fail on finding layers and region edges in OCT images. The overcomplete-wavelet-frame-based fractal signature method based on high-pass information and a fuzzy-c-mean algorithm is considered to avoid the threshold processing, but the high-pass information is distorted because of noises and diffusions. To improve the high-pass information distortion problem, the proposed method uses the mean value and an enhanced-fuzzy-c-mean algorithm to cluster pixels in 2-D OCT images and find the edge between different clustered regions. The vessel OCT images are tested in the experiment, and the experimental results show that the proposed method performs with more accurate segmentation results than the overcomplete-wavelet-frame-based fractal signature method.

引用

页码：35 / 39

页数：5

共 7 条

[1] Automated 3-D Intraretinal Layer Segmentation of Macular Spectral-Domain Optical Coherence Tomography Images [J].