Jingyu Liu, Huaiyu Cai, Wenyue Hao, Tingtao Zuo, Zhongwei Jia, Yi Wang, Xiaodong Chen. Intravascular ultrasound image segmentation combining polar coordinate modeling and a neural network[J]. Opto-Electronic Engineering, 2023, 50(1): 220118
- Opto-Electronic Engineering
- Vol. 50, Issue 1, 220118 (2023)
Fig. 1. Ideal hypothesis diagrams. (a) The mask image that meets the ideal hypothesis; (b) The situation that does not meet the ideal hypothesis
Fig. 2. Modeling schematics. (a) Original image of IVUS; (b) Schematic diagram of modeling result. The intima contour and media contour are marked with red and green curves, respectively. The modeling results of the lumen area and plaque area are marked with red and green line segments, respectively
Fig. 3. The proposed dense distance of regression network
Fig. 4. Schematic diagram of the intersection of the true value and the predicted value patch area. Note: For the convenience of observation, the true value ray and the predicted value ray are staggered by a certain angle, and the two are actually on the same ray
Fig. 5. The graph of JM changing with the number of rays
Fig. 6. Visualization of segmentation results of different modeling methods
Fig. 7. Comparison of the visual effects of the segmentation results
Fig. 8. Linear regression analysis of key clinical parameters
Fig. 9. Bland-Altman analysis of key clinical parameters
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Table 1. Information of the IVUS dataset
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Table 2. The performance of the proposed method under different depths of backbone and different numbers of SEB modules
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Table 3. Experimental results with different loss functions
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Table 4. Experimental results with different modeling methods
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Table 5. Performance comparison of different segmentation models
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Table 6. Results of linear regression analysis of key clinical parameters
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Table 7. Results of Bland-Altman analysis of key clinical parameters
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