Chinese Journal of Magnetic Resonance ›› 2023, Vol. 40 ›› Issue (3): 270-279.doi: 10.11938/cjmr20223047
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TIAN Hui1,WU Jie1,*(),BIAN Yun2,#(),ZHANG Zhiwei1,SHAO Chengwei2
Received:
2022-12-18
Published:
2023-09-05
Online:
2023-03-22
Contact:
*Tel: 021-55271116, E-mail: CLC Number:
TIAN Hui, WU Jie, BIAN Yun, ZHANG Zhiwei, SHAO Chengwei. Classification of Pancreatic Cystic Tumors Based on DenseNet and Transfer Learning[J]. Chinese Journal of Magnetic Resonance, 2023, 40(3): 270-279.
Table 1
DenseNet161 network structure
Layers | DenseNet161 |
---|---|
Convolution | 7×7 conv |
Pooling | 3×3 max pool |
Dense Block 1 | $\left[ \begin{matrix} 1\times 1\ \text{conv} \\ 3\times 3\ \text{conv} \\ \end{matrix} \right]\times 6$ |
Transition Layer 1 | 1×1 conv, 2×2 average pool |
Dense Block 2 | $\left[ \begin{matrix} 1\times 1\ \text{conv} \\ 3\times 3\ \text{conv} \\ \end{matrix} \right]\times 12$ |
Transition Layer 2 | 1×1 conv, 2×2 average pool |
Dense Block 3 | $\left[ \begin{matrix} 1\times 1\ \text{conv} \\ 3\times 3\ \text{conv} \\ \end{matrix} \right]\times 36$ |
Transition Layer 3 | 1×1 conv, 2×2 average pool |
Dense Block 4 | $\left[ \begin{matrix} 1\times 1\ \text{conv} \\ 3\times 3\ \text{conv} \\ \end{matrix} \right]\times 24$ |
Classification Layer | 7×7 global average pool, fully-connected, softmax |
Table 4
Experimental results of MCN and SCN recognition by different deep learning models
模型 | ACC | Precision | Recall | Specificity | F1-Score | AUC | 参数量 |
---|---|---|---|---|---|---|---|
AlexNet | 0.844 | 0.846 | 0.842 | 0.847 | 0.844 | 0.930 | 6100840 |
MobileNet_v3 | 0.889 | 0.894 | 0.884 | 0.895 | 0.889 | 0.960 | 5483032 |
Vgg16 | 0.898 | 0.907 | 0.886 | 0.909 | 0.896 | 0.966 | 138365992 |
ResNet50 | 0.912 | 0.923 | 0.898 | 0.926 | 0.910 | 0.971 | 25557032 |
本文 | 0.943 | 0.938 | 0.949 | 0.937 | 0.943 | 0.989 | 28681000 |
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