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Table 1 Classification accuracy and F1 scores of Inception v3, ResNet101 and DenseNet201 convolutional neural networks on calcified plaques with motion artifacts of four densities

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

Plaque density Inception v3 ResNet101 DenseNet201
Accuracy F1 score Accuracy F1 score Accuracy F1 score
High 88.8 ± 2.3% 0.917 ± 0.024 90.2 ± 2.8% 0.922 ± 0.027 89.3 ± 2.9% 0.919 ± 0.023
Medium-1 88.0 ± 3.0% 0.901 ± 0.022 87.1 ± 2.3% 0.896 ± 0.020 87.7 ± 2.9% 0.897 ± 0.021
Medium-2 90.7 ± 2.5% 0.939 ± 0.024 92.9 ± 2.9% 0.942 ± 0.028 90.7 ± 2.0% 0.937 ± 0.018
Low 93.3 ± 1.6% 0.950 ± 0.012 92.4 ± 2.8% 0.947 ± 0.020 92.7 ± 2.8% 0.945 ± 0.019
  1. Variables are displayed as mean ± standard deviation