Journal of Computer Applications ›› 2023, Vol. 43 ›› Issue (10): 3282-3289.DOI: 10.11772/j.issn.1001-9081.2022101545
• Multimedia computing and computer simulation • Previous Articles
Xiaoyan LU1, Yang XU1,2(), Wenhao YUAN1
Received:
2022-10-14
Revised:
2023-02-06
Accepted:
2023-02-08
Online:
2023-04-12
Published:
2023-10-10
Contact:
Yang XU
About author:
LU Xiaoyan, born in 1997, M. S. candidate. Her research interests include deep learning, image processing.Supported by:
通讯作者:
徐杨
作者简介:
卢小燕(1997—),女,河南南阳人,硕士研究生,主要研究方向:深度学习、图像处理基金资助:
CLC Number:
Xiaoyan LU, Yang XU, Wenhao YUAN. Multiscale dense fusion network for lung lesion image segmentation[J]. Journal of Computer Applications, 2023, 43(10): 3282-3289.
卢小燕, 徐杨, 袁文昊. 用于肺部病灶图像分割的多尺度稠密融合网络[J]. 《计算机应用》唯一官方网站, 2023, 43(10): 3282-3289.
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URL: http://www.joca.cn/EN/10.11772/j.issn.1001-9081.2022101545
数据集 | 网络 | ACC | MIoU | DSC | F1 |
---|---|---|---|---|---|
Lung dataset-1 | SegNet | 73.7 | 69.8 | 61.3 | 53.6 |
R2U-Net | 77.1 | 71.0 | 62.5 | 57.8 | |
Attention U-Net | 79.9 | 73.3 | 64.1 | 60.5 | |
U2-Net | 81.2 | 75.9 | 67.6 | 63.9 | |
CaraNet | 81.7 | 76.5 | 68.3 | 65.2 | |
UNeXt | 82.4 | 79.2 | 70.5 | 68.6 | |
MDF-Net | 83.6 | 82.3 | 73.4 | 70.3 | |
Lung dataset-2 | SegNet | 85.6 | 75.9 | 66.2 | 57.1 |
R2U-Net | 87.3 | 82.6 | 72.3 | 68.3 | |
Attention U-Net | 88.9 | 83.5 | 74.7 | 70.5 | |
U2-Net | 89.4 | 84.3 | 75.1 | 72.4 | |
CaraNet | 89.6 | 86.4 | 76.5 | 72.9 | |
UNeXt | 91.8 | 89.5 | 78.8 | 73.7 | |
MDF-Net | 93.1 | 91.2 | 79.9 | 75.2 |
Tab. 1 Performance comparison of different networks on Lung dataset-1 and Lung dataset-2
数据集 | 网络 | ACC | MIoU | DSC | F1 |
---|---|---|---|---|---|
Lung dataset-1 | SegNet | 73.7 | 69.8 | 61.3 | 53.6 |
R2U-Net | 77.1 | 71.0 | 62.5 | 57.8 | |
Attention U-Net | 79.9 | 73.3 | 64.1 | 60.5 | |
U2-Net | 81.2 | 75.9 | 67.6 | 63.9 | |
CaraNet | 81.7 | 76.5 | 68.3 | 65.2 | |
UNeXt | 82.4 | 79.2 | 70.5 | 68.6 | |
MDF-Net | 83.6 | 82.3 | 73.4 | 70.3 | |
Lung dataset-2 | SegNet | 85.6 | 75.9 | 66.2 | 57.1 |
R2U-Net | 87.3 | 82.6 | 72.3 | 68.3 | |
Attention U-Net | 88.9 | 83.5 | 74.7 | 70.5 | |
U2-Net | 89.4 | 84.3 | 75.1 | 72.4 | |
CaraNet | 89.6 | 86.4 | 76.5 | 72.9 | |
UNeXt | 91.8 | 89.5 | 78.8 | 73.7 | |
MDF-Net | 93.1 | 91.2 | 79.9 | 75.2 |
数据集 | 模块 | ACC | MIoU | DSC | F1 | ||||
---|---|---|---|---|---|---|---|---|---|
基础网络 | UR | M1 | M2 | IWF | |||||
Lung dataset-1 | √ | 74.7 | 74.1 | 67.2 | 67.4 | ||||
√ | √ | 75.6 | 75.2 | 68.9 | 68.2 | ||||
√ | √ | 77.2 | 76.1 | 70.5 | 68.4 | ||||
√ | √ | √ | √ | 79.9 | 78.2 | 71.3 | 69.5 | ||
√ | √ | √ | √ | √ | 83.6 | 82.3 | 73.4 | 70.3 | |
Lung dataset-1 | √ | 84.9 | 82.3 | 72.5 | 72.8 | ||||
√ | √ | 85.6 | 83.5 | 74.4 | 73.5 | ||||
√ | √ | 86.1 | 84.9 | 76.7 | 73.6 | ||||
√ | √ | √ | √ | 89.7 | 87.3 | 78.2 | 74.1 | ||
√ | √ | √ | √ | √ | 93.1 | 91.2 | 79.9 | 75.2 |
Tab. 2 Influence of different modules on network performance on Lung dataset-1 and Lung dataset-2
数据集 | 模块 | ACC | MIoU | DSC | F1 | ||||
---|---|---|---|---|---|---|---|---|---|
基础网络 | UR | M1 | M2 | IWF | |||||
Lung dataset-1 | √ | 74.7 | 74.1 | 67.2 | 67.4 | ||||
√ | √ | 75.6 | 75.2 | 68.9 | 68.2 | ||||
√ | √ | 77.2 | 76.1 | 70.5 | 68.4 | ||||
√ | √ | √ | √ | 79.9 | 78.2 | 71.3 | 69.5 | ||
√ | √ | √ | √ | √ | 83.6 | 82.3 | 73.4 | 70.3 | |
Lung dataset-1 | √ | 84.9 | 82.3 | 72.5 | 72.8 | ||||
√ | √ | 85.6 | 83.5 | 74.4 | 73.5 | ||||
√ | √ | 86.1 | 84.9 | 76.7 | 73.6 | ||||
√ | √ | √ | √ | 89.7 | 87.3 | 78.2 | 74.1 | ||
√ | √ | √ | √ | √ | 93.1 | 91.2 | 79.9 | 75.2 |
数据集 | 采样方式 | ACC | MIoU | DSC | F1 |
---|---|---|---|---|---|
Lung dataset-1 | upsampling | 74.7 | 74.1 | 67.2 | 67.4 |
UR | 75.6 | 75.2 | 68.9 | 68.2 | |
Lung dataset-2 | upsampling | 84.9 | 82.3 | 72.5 | 72.8 |
UR | 85.6 | 83.5 | 74.4 | 73.5 |
Tab. 3 Performance comparison of different upsampling methods on Lung dataset-1 and Lung dataset-2
数据集 | 采样方式 | ACC | MIoU | DSC | F1 |
---|---|---|---|---|---|
Lung dataset-1 | upsampling | 74.7 | 74.1 | 67.2 | 67.4 |
UR | 75.6 | 75.2 | 68.9 | 68.2 | |
Lung dataset-2 | upsampling | 84.9 | 82.3 | 72.5 | 72.8 |
UR | 85.6 | 83.5 | 74.4 | 73.5 |
数据集 | UR模块组成 | ACC | MIoU | DSC | F1 |
---|---|---|---|---|---|
Lung dataset-1 | 无 | 74.7 | 74.1 | 67.2 | 67.4 |
M3 | 75.2 | 74.8 | 68.4 | 67.9 | |
M4 | 74.9 | 74.5 | 67.7 | 67.6 | |
UR | 75.6 | 75.2 | 68.9 | 68.2 | |
Lung dataset-2 | 无 | 84.9 | 82.3 | 72.5 | 72.8 |
M3 | 85.3 | 83.1 | 73.8 | 73.3 | |
M4 | 85.1 | 82.6 | 73.2 | 73.0 | |
UR | 85.6 | 83.5 | 74.4 | 73.5 |
Tab. 4 Performance comparison of different components of UR module on Lung dataset-1 and Lung dataset-2
数据集 | UR模块组成 | ACC | MIoU | DSC | F1 |
---|---|---|---|---|---|
Lung dataset-1 | 无 | 74.7 | 74.1 | 67.2 | 67.4 |
M3 | 75.2 | 74.8 | 68.4 | 67.9 | |
M4 | 74.9 | 74.5 | 67.7 | 67.6 | |
UR | 75.6 | 75.2 | 68.9 | 68.2 | |
Lung dataset-2 | 无 | 84.9 | 82.3 | 72.5 | 72.8 |
M3 | 85.3 | 83.1 | 73.8 | 73.3 | |
M4 | 85.1 | 82.6 | 73.2 | 73.0 | |
UR | 85.6 | 83.5 | 74.4 | 73.5 |
数据集 | 注意力模块 | ACC | MIoU | DSC | F1 |
---|---|---|---|---|---|
Lung dataset-1 | 无 | 74.7 | 74.1 | 67.2 | 67.4 |
SCSE | 74.9 | 74.3 | 67.6 | 67.7 | |
ECA | 74.6 | 73.5 | 66.3 | 59.8 | |
自注意力金字塔模块 | 77.2 | 76.1 | 70.5 | 68.4 | |
Lung dataset-2 | 无 | 84.9 | 82.3 | 72.5 | 72.8 |
SCSE | 85.2 | 84.1 | 75.9 | 72.4 | |
ECA | 84.5 | 81.6 | 71.2 | 62.9 | |
自注意力金字塔模块 | 86.1 | 84.9 | 76.7 | 73.6 |
Tab. 5 Performance comparison of different attention modules on Lung dataset-1 and Lung dataset-2
数据集 | 注意力模块 | ACC | MIoU | DSC | F1 |
---|---|---|---|---|---|
Lung dataset-1 | 无 | 74.7 | 74.1 | 67.2 | 67.4 |
SCSE | 74.9 | 74.3 | 67.6 | 67.7 | |
ECA | 74.6 | 73.5 | 66.3 | 59.8 | |
自注意力金字塔模块 | 77.2 | 76.1 | 70.5 | 68.4 | |
Lung dataset-2 | 无 | 84.9 | 82.3 | 72.5 | 72.8 |
SCSE | 85.2 | 84.1 | 75.9 | 72.4 | |
ECA | 84.5 | 81.6 | 71.2 | 62.9 | |
自注意力金字塔模块 | 86.1 | 84.9 | 76.7 | 73.6 |
数据集 | 特征融合模块 | ACC | MIoU | DSC | F1 |
---|---|---|---|---|---|
Lung dataset-1 | 无 | 79.9 | 78.2 | 71.3 | 69.5 |
FFM | 80.3 | 78.8 | 71.6 | 69.8 | |
MAFF | 81.2 | 80.1 | 72.5 | 70.2 | |
IWF | 83.6 | 82.3 | 73.4 | 70.3 | |
Lung dataset-2 | 无 | 89.7 | 87.3 | 78.2 | 74.1 |
FFM | 90.6 | 88.5 | 78.6 | 74.3 | |
MAFF | 92.5 | 89.7 | 79.2 | 74.8 | |
IWF | 93.1 | 91.2 | 79.9 | 75.2 |
Tab. 6 Performance comparison of IWF module and other feature fusion modules on Lung dataset-1 and Lung dataset-2
数据集 | 特征融合模块 | ACC | MIoU | DSC | F1 |
---|---|---|---|---|---|
Lung dataset-1 | 无 | 79.9 | 78.2 | 71.3 | 69.5 |
FFM | 80.3 | 78.8 | 71.6 | 69.8 | |
MAFF | 81.2 | 80.1 | 72.5 | 70.2 | |
IWF | 83.6 | 82.3 | 73.4 | 70.3 | |
Lung dataset-2 | 无 | 89.7 | 87.3 | 78.2 | 74.1 |
FFM | 90.6 | 88.5 | 78.6 | 74.3 | |
MAFF | 92.5 | 89.7 | 79.2 | 74.8 | |
IWF | 93.1 | 91.2 | 79.9 | 75.2 |
数据集 | 网络 | ACC | MIoU | DSC | F1 |
---|---|---|---|---|---|
Lung dataset-1 | UNet++ | 80.9 | 79.4 | 70.1 | 66.3 |
MDF-Net | 83.6 | 82.3 | 73.4 | 70.3 | |
Lung dataset-2 | UNet++ | 89.1 | 88.7 | 76.9 | 71.4 |
MDF-Net | 93.1 | 91.2 | 79.9 | 75.2 |
Tab. 7 Performance comparison of dense connection methods of two networks on Lung dataset-1 and Lung dataset-2
数据集 | 网络 | ACC | MIoU | DSC | F1 |
---|---|---|---|---|---|
Lung dataset-1 | UNet++ | 80.9 | 79.4 | 70.1 | 66.3 |
MDF-Net | 83.6 | 82.3 | 73.4 | 70.3 | |
Lung dataset-2 | UNet++ | 89.1 | 88.7 | 76.9 | 71.4 |
MDF-Net | 93.1 | 91.2 | 79.9 | 75.2 |
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