Classification of Diabetic Retinopathy with Feature Fusion Network

Fig. 2. Four types of images in the APTOS dataset. (a) Rectangular image, no cropping; (b) rectangular image, lossy vertical cropping; (c) square image, tight cropping; (d) rectangular image, lossy vertical and horizontal cropping

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Fig. 3. Preprocessed images

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Fig. 4. Overall network architecture

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Fig. 5. Multi-scale channel attention module

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Fig. 6. Loss curve

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Fig. 7. Confusion matrix

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Table 1. Distribution of APTOS 2019 dataset
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Table 1. Distribution of APTOS 2019 dataset
Label Number of images
No DR 1805
Mild DR 370
Moderate DR 999
Severe DR 193
Proliferative DR 295

Table 2. Network architecture of EfficientNet-B0 (stage1-8)

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Table 2. Network architecture of EfficientNet-B0 (stage1-8)

Stage	Operateor	k×k	Output size	Number of layers
1	Conv	3×3	256×256×32	×1
2	MBConvBlock1	3×3	128×128×16	×1
3	MBConvBlock6	3×3	128×128×24	×2
4	MBConvBlock6	5×5	64×64×40	×2
5	MBConvBlock6	3×3	32×32×80	×3
6	MBConvBlock6	5×5	16×16×112	×3
7	MBConvBlock6	5×5	16×16×192	×4
8	MBConvBlock6	3×3	8×8×320	×1

Table 3. Ablation study
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Table 3. Ablation study
Model Accuracy Recall Precision
EfficientNet-B0 83.92 62.33 78.94
EfficientNet-B0+Dilated convolution 84.74 64.68 77.08
Proposed model 85.25 68.41 82.20

Table 4. Result comparison with existing researches
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Table 4. Result comparison with existing researches
Model Accuracy Recall Precision
ResNet-50^［34］ 73.778
SE-Net^［34］ 72.873
SE-ResNet-50^［34］ 76.144
Model in Ref.［23］ 80.06 80.00 81.00
Model in Ref.［25］ 83.09
Proposed model 85.25 68.41 82.20

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Shuang Zhao, Ge Mu, Wenhua Zhao, Zhiqing Ma. Classification of Diabetic Retinopathy with Feature Fusion Network[J]. Laser & Optoelectronics Progress, 2023, 60(14): 1417001

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