Laser & Optoelectronics Progress, Volume. 59, Issue 16, 1617001(2022)
Video Nystagmus Classification Algorithm Based on Attention Mechanism
Figures & Tables(13)
Fig. 8. Relationship between loss value and accuracy of different loss functions and number of iterations. (a) Loss value; (b) accuracy
Table 1. Proposed BPPV nystagmus video classification algorithm framework
View tableTable 1. Proposed BPPV nystagmus video classification algorithm framework
Layer/Stride Repeat Output size Input 3×16×224×224 Conv（3×3×3）/2 1 32×16×112×112 Inverted Residual Block/2 1 16×16×56×56 NL Block/1 2 16×16×56×56 Inverted Residual Block/2 2 24×8×28×28 Inverted Residual Block/2 3 32×8×14×14 Inverted Residual Block/2 4 64×2×7×7 Inverted Residual Block/1 3 96×2×7×7 Inverted Residual Block/2 2 160×1×4×4 SE Inverted Residual Block/1 2 160×1×4×4 Inverted Residual Block/2 1 320×1×4×4 Conv（3×3×3）/1 1 1280×1×4×4 AvgPool/1 1 1280×1×1×1 Linear 1 N Classes
Table 2. Label description of data set
View tableTable 2. Label description of data set
Mode 0 1 2 Horizontal Left Right None Vertical Up Down None Axial Clockwise Counterclockwise None Intensity From weak to strong From strong to weak None
Table 3. Performance of mainstream 3D convolutional neural networks on nystagmus video classification dataset
View tableTable 3. Performance of mainstream 3D convolutional neural networks on nystagmus video classification dataset
Algorithm Number of parameters /MB Accuracy C3D［ 31 ］34.80 0.8443 3D ResNet18［ 32 ］33.24 0.8518 3D ResNet34［ 32 ］63.55 0.8717 3D SqueezeNet［ 33 ］1.87 0.8625 3D ShuffleNetV2［ 34 ］1.37 0.8502 3D MobileNetV2 2.44 0.8791 Proposed algorithm 2.65 0.9085
Table 4. Influence of different modules on the model
View tableTable 4. Influence of different modules on the model
Condition Accuracy 3D MobileNet V2 0.8791 3D MobileNet V2 +NL Block 0.8922 3D MobileNet V2 +3D SE Inverted Residual Block 0.8853 3D MobileNet V2 +NL Block +3D SE Inverted Residual Block 0.9085
Table 5. The performance of the proposed algorithm in each category
View tableTable 5. The performance of the proposed algorithm in each category
Label Precision Recall F1-score N Label Precision Recall F1-score N 0000 0.500 1.000 0.667 27 1111 1.000 0.933 0.966 71 0001 0.810 0.708 0.756 123 1112 1.000 1.000 1.000 251 0002 0.854 0.875 0.864 150 1120 0.864 1.000 0.927 74 0010 1.000 1.000 1.000 50 1121 1.000 0.927 0.962 190 0011 0.953 0.968 0.961 371 1122 0.972 0.977 0.975 782 0012 0.955 0.955 0.955 350 1200 0.700 1.000 0.824 45 0020 0.833 0.833 0.833 30 1201 0.867 0.929 0.897 128 0021 1.000 1.000 1.000 100 1202 0.984 0.918 0.950 673 0022 0.976 0.953 0.965 226 1210 0.500 0.400 0.444 13 0101 2 1212 0.857 0.750 0.800 21 0110 0.909 1.000 0.952 84 1220 0.800 0.821 0.810 1280 0111 0.968 0.989 0.978 426 1221 0.830 0.855 0.843 1742 0112 0.947 0.957 0.952 455 1222 0.907 0.874 0.890 2387 0120 1.000 0.933 0.966 60 2000 1.000 0.667 0.800 6 0121 0.952 1.000 0.976 145 2001 1.000 1.000 1.000 29 0122 0.981 0.963 0.972 877 2002 1.000 1.000 1.000 7 0210 0.857 0.857 0.857 51 2010 0.250 1.000 0.400 10 0211 1.000 0.933 0.966 237 2011 1.000 0.818 0.900 32 0212 0.955 0.980 0.967 767 2012 0.500 0.667 0.571 21 0220 0.853 0.871 0.862 1240 2021 1.000 1.000 1.000 29 0221 0.901 0.856 0.878 1746 2022 0.977 1.000 0.988 169 0222 0.878 0.904 0.891 2434 2101 1.000 1.000 1.000 11 1001 1.000 0.979 0.989 249 2102 3 1002 0.953 0.943 0.948 398 2110 1.000 1.000 1.000 12 1010 1.000 0.636 0.778 51 2111 1.000 1.000 1.000 45 1011 0.921 0.946 0.933 114 2112 1.000 1.000 1.000 190 1012 0.889 0.930 0.909 259 2120 1.000 1.000 1.000 6 1020 1.000 1.000 1.000 13 2122 1.000 1.000 1.000 276 1021 1.000 0.862 0.926 136 2201 5 1022 0.986 0.986 0.986 395 2202 1.000 0.857 0.923 32 1100 0.881 0.952 0.915 263 2211 1.000 1.000 1.000 8 1101 0.904 0.881 0.893 540 2212 0.500 1.000 0.667 5 1102 0.921 0.925 0.923 1071 2222 0.976 1.000 0.988 200
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Haojun Zhou, Xiaoli Zhao, Yongbin Gao, Haibo Li, Ruoran Cheng. Video Nystagmus Classification Algorithm Based on Attention Mechanism[J]. Laser & Optoelectronics Progress, 2022, 59(16): 1617001
Paper Information
Category: Medical Optics and Biotechnology
Received: May. 7, 2021
Accepted: Jul. 13, 2021
Published Online: Jul. 22, 2022
The Author Email: Xiaoli Zhao (evawhy@163.com)
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