Laser & Optoelectronics Progress, Volume. 56, Issue 16, 161014(2019)

Ultrasound Left Ventricular Segmentation Method Based on Multi-Phase Level Set

Ke Wu** and Ling Yang*
Author Affiliations
  • College of Electronic Engineering, Chengdu University of Information Technology, Chengdu, Sichuan 610200, China
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    Figures & Tables(6)
    Result of binary image processing. (a) Segmentation result of three-phase Level Set; (b) take out results of white part of Fig. 1(a); (c) parabolic model; (d) left ventricular full filling image; (c) result of binary image processing
    Flow chart of algorithm
    Comparison of segmentation results of different algorithms with doctor's manual segmentation results. (a) Segmentation result of traditional Level Set method for low noise image; (b) segmentation result of proposed method for low noise image; (c) doctor's manual segmentation result for low noise image; (d) segmentation result of traditional Level Set method for high noise image; (e) segmentation result of proposed method for high noise image; (f) doctor's manual segmentation result for high nois
    Results of left ventricular segmentation. (a) Original image; (b) three-phase Level Set segmentation; (c) binarization; (d) binary image subsequent processing; (e) segmentation result
    Linear fitting results for different numbers of sample points. (a) 5; (b) 10; (c) 15; (d) 20; (e) 30
    • Table 1. Results of different evaluation parameter

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      Table 1. Results of different evaluation parameter

      AlgorithmAverage precision /%
      RDDRODDice
      Three-phaseLevel Set0.051±0.0210.883±0.0450.897±0.040
      Level Set0.108±0.0710.793±0.0850.821±0.079
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    Ke Wu, Ling Yang. Ultrasound Left Ventricular Segmentation Method Based on Multi-Phase Level Set[J]. Laser & Optoelectronics Progress, 2019, 56(16): 161014

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    Paper Information

    Category: Image Processing

    Received: Feb. 28, 2019

    Accepted: Mar. 27, 2019

    Published Online: Aug. 5, 2019

    The Author Email: Ke Wu (wukecap@163.com), Ling Yang (cimyang@cuit.edu.cn)

    DOI:10.3788/LOP56.161014

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