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
- Acta Optica Sinica
- Vol. 40, Issue 6, 0610001 (2020)
Fig. 1. Schematic diagram of 3D-HDC-Unet model structure
Fig. 2. Dot product operation diagram of 3D convolution with input voxel block. (a) Original 3D convolution operation; (b) 2-dilated 3D convolution operation
Fig. 3. Hybrid dilated convolutional residual module
Fig. 4. 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.
Fig. 5. Effect of γ on attenuated loss
Fig. 6. 5-fold cross-validation
Fig. 7. 3D-HDC-Unet test set DSC box diagram
Fig. 8. Algorithm flowchart and image processing results of each stage
Fig. 9. Segmentation result diagram
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Table 1. Ratio of different types of voxels to total voxel in the BraTS 2017 dataset
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Table 2. Comparison of evaluation index data of eight models
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