Acta Optica Sinica, Volume. 40, Issue 6, 0610001(2020)

Automatic Segmentation Algorithm for Multimodal Magnetic Resonance-Based Brain Tumor Images

Cheng'en He*, Huijun Xu**, Zhong Wang***, and Liping Ma
Author Affiliations
  • College of Electrical Engineering, Sichuan University, Chengdu, Sichuan 610065, China
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    Figures & Tables(11)
    Schematic diagram of 3D-HDC-Unet model structure
    Dot product operation diagram of 3D convolution with input voxel block. (a) Original 3D convolution operation; (b) 2-dilated 3D convolution operation
    Hybrid dilated convolutional residual module
    Sketch map of input images sub-sampling and HDC receptive fieldNote:In layer 3 4 5, the size of images is enlarged to scale for better demonstration.
    Effect of γ on attenuated loss
    5-fold cross-validation
    3D-HDC-Unet test set DSC box diagram
    Algorithm flowchart and image processing results of each stage
    Segmentation result diagram
    • Table 1. Ratio of different types of voxels to total voxel in the BraTS 2017 dataset

      View table

      Table 1. Ratio of different types of voxels to total voxel in the BraTS 2017 dataset

      LabelLabel 0Label1Label 2Label 4
      Percentage /%960.82.40.8
    • Table 2. Comparison of evaluation index data of eight models

      View table

      Table 2. Comparison of evaluation index data of eight models

      ModelDSCSensitivitySpecificityHausdorff distance
      WTTCETWTTCETWTTCETWTTCET
      Two-path 3D CNN[21]0.850.780.730.800.760.750.970.970.9610.615.47.70
      3D-Unet[22]0.880.760.720.900.780.750.980.980.9813.622.313.8
      3D-Unet+HDC0.900.750.710.920.780.730.990.990.976.067.855.33
      K-means[23]0.79--0.94--0.98-----
      Hybrid level set[23]0.80--0.77--0.98-----
      Hybrid algorithm[24]0.90--0.89--0.98-----
      Random forests[24]0.860.780.660.830.720.570.990.990.997.618.703.76
      Proposed method0.900.800.770.920.840.810.990.990.976.067.695.20
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    Cheng'en He, Huijun Xu, Zhong Wang, Liping Ma. Automatic Segmentation Algorithm for Multimodal Magnetic Resonance-Based Brain Tumor Images[J]. Acta Optica Sinica, 2020, 40(6): 0610001

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    Paper Information

    Category: Image Processing

    Received: Aug. 19, 2019

    Accepted: Nov. 28, 2019

    Published Online: Mar. 6, 2020

    The Author Email: He Cheng'en (530208058@qq.com), Xu Huijun (839000429@qq.com), Wang Zhong (1648277629@qq.com)

    DOI:10.3788/AOS202040.0610001

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