標題: Vessel segmentation in 2-D optical coherence tomography images
作者: Liu, Li-chang
Lee, Jiann-der
Hsu, Yu-wei
Tseng, Scott
Tseng, Ellen
Tsai, Meng-tsan
電子工程學系及電子研究所
Department of Electronics Engineering and Institute of Electronics
關鍵字: Optical coherence tomography;OCT;texture segmentation;fuzzy-c-mean;vessel
公開日期: 1-一月-2013
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.
URI: http://hdl.handle.net/11536/146355
期刊: 2013 ICME INTERNATIONAL CONFERENCE ON COMPLEX MEDICAL ENGINEERING (CME)
起始頁: 35
結束頁: 39
顯示於類別:會議論文