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Laser & Optoelectronics Progress, Volume. 55, Issue 5, 051701(2018)

Research and Realization of Local Cardiovascular Computed Tomography Extraction Algorithm in Lesion Assisted Diagnosis

Guoyin Ren1、1; , Xiaoqi Lü1、1; , Nan Yang1、2; , and Dahua Yu1、1;
Author Affiliations
  • 1 Foreign Language Department, Baotou Medical College, Baotou, Inner Mongolia 0 14010, China
  • 1 School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia 0 14010, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (11)
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    References (18)
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    Figures & Tables(11)
    Flow chart of improved parallel region growing algorithm

    Fig. 1. Flow chart of improved parallel region growing algorithm

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    Composition of MEA

    Fig. 2. Composition of MEA

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    Constraint effect of pixel edges. (a) Blood vessel seed point setting; (b) blood vessel segmentation before g value constraint; (c) blood vessel segmentation after g value constraint

    Fig. 3. Constraint effect of pixel edges. (a) Blood vessel seed point setting; (b) blood vessel segmentation before g value constraint; (c) blood vessel segmentation after g value constraint

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    Flow chart of cardiac lesion vascular extraction and four-dimensional visualization

    Fig. 4. Flow chart of cardiac lesion vascular extraction and four-dimensional visualization

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    Dynamic rendering results for four-dimensional CT of heart

    Fig. 5. Dynamic rendering results for four-dimensional CT of heart

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    Extraction results of local cardiac lesion area. (a) Extraction of local three-dimensional tissue; (b) the area of interest drawn with mouse

    Fig. 6. Extraction results of local cardiac lesion area. (a) Extraction of local three-dimensional tissue; (b) the area of interest drawn with mouse

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    Results of local cardiac blood vessels (a) before and (b) after resampling

    Fig. 7. Results of local cardiac blood vessels (a) before and (b) after resampling

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    Four-dimensional extraction results of blood vessels

    Fig. 8. Four-dimensional extraction results of blood vessels

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    Time comparison of parallel region growing algorithm before and after improvement

    Fig. 9. Time comparison of parallel region growing algorithm before and after improvement

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    Robustness analysis of the system after disturbance

    Fig. 10. Robustness analysis of the system after disturbance

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    • Table 1. Four-dimensional display performance of heart and local vessels

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      Table 1. Four-dimensional display performance of heart and local vessels

      Data setPhase volumedata numberResolution /pixelDisplay time /sFPS
      MaximumMinimum
      Heart data4256×256×256×40.92824.5818.87
      8256×256×256×81.39920.7516.39
      10256×256×256×101.62218.3413.78
      ROINon-resampling1060×40×126×101.61531.8722.73
      Resampling1060×40×126×101.70230.5721.21
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    Guoyin Ren, Xiaoqi Lü, Nan Yang, Dahua Yu. Research and Realization of Local Cardiovascular Computed Tomography Extraction Algorithm in Lesion Assisted Diagnosis[J]. Laser & Optoelectronics Progress, 2018, 55(5): 051701

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    Paper Information

    Category: Medical optics and biotechnology

    Received: Sep. 22, 2017

    Accepted: --

    Published Online: Sep. 11, 2018

    The Author Email: Guoyin Ren (renguoyin@imust.edu.cn)

    DOI:10.3788/LOP55.051701

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology