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  • Received: Oct. 18, 2018

    Accepted: Mar. 1, 2019

    Posted: May. 20, 2019

    Published Online: May. 20, 2019

    The Author Email: Jian Yang (jyang@bit.edu.cn)

    DOI: 10.3788/COL201917.051001

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    Yong Huang, Chuanchao Wu, Shaoyan Xia, Lu Liu, Shanlin Chen, Dedi Tong, Danni Ai, Jian Yang, Yongtian Wang. Boundary segmentation based on modified random walks for vascular Doppler optical coherence tomography images[J]. Chinese Optics Letters, 2019, 17(5): 051001

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Chinese Optics Letters, Vol. 17, Issue 5, 051001 (2019)

Boundary segmentation based on modified random walks for vascular Doppler optical coherence tomography images

Yong Huang1,2, Chuanchao Wu1,2, Shaoyan Xia1,2, Lu Liu3, Shanlin Chen3, Dedi Tong3, Danni Ai1, Jian Yang1,*, and Yongtian Wang1,2

Author Affiliations

  • 1Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
  • 2Key Laboratory of Photoelectronic Imaging Technology and System (Beijing Institute of Technology), Ministry of Education, Beijing 100081, China
  • 3Department of Hand Surgery, Beijing Ji Shui Tan Hospital, Beijing 100035, China

Abstract

Vascular Doppler optical coherence tomography (DOCT) images with weak boundaries are usually difficult for most algorithms to segment. We propose a modified random walk (MRW) algorithm with a novel regularization for the segmentation of DOCT vessel images. Based on MRW, we perform automatic boundary detection of the vascular wall from intensity images and boundary extraction of the blood flowing region from Doppler phase images. Dice, sensitivity, and specificity coefficients were adopted to verify the segmentation performance. The experimental study on DOCT images of the mouse femoral artery showed the effectiveness of our proposed method, yielding three-dimensional visualization and quantitative evaluation of the vessel.

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