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Table 3 Classification accuracy of Inception v3, ResNet101 and DenseNet201 convolutional neural network on calcified plaques with motion artifacts on four CT systems

From: Classification of moving coronary calcified plaques based on motion artifacts using convolutional neural networks: a robotic simulating study on influential factors

 

Inception v3

ResNet101

DenseNet201

CT-A

90.2 ± 3.1%

92.2 ± 2.3%

92.0 ± 1.8%

CT-B

89.8 ± 2.7%

88.0 ± 5.3%

89.3 ± 5.6%

CT-C

91.0 ± 2.8%

90.9 ± 2.6%

90.7 ± 2.4%

CT-D

91.8 ± 0.8%

91.2 ± 3.6%

91.1 ± 2.6%

  1. Variables are displayed as mean ± standard deviation
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BMC Medical Imaging

ISSN: 1471-2342

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