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. 2020 Jan 22;2(1):e190015. doi: 10.1148/ryai.2019190015

Figure 2:

Validation set area under the receiver operating characteristic curve (AUROC) for six different diagnostic labels shows improved performance with increased image resolution and a plateau effect on performance improvement for resolutions higher than 224 × 224 pixels. Models were trained with ResNet34 architecture for three subsample epochs. Resolutions shown are as follows: 32 × 32, 64 × 64, 128 × 128, 224 × 224, 256 × 256, 320 × 320, 448 × 448, 512 × 512, and 600 × 600 pixels. Error bars represent standard deviation of the area under the curve calculated via the DeLong method.

Validation set area under the receiver operating characteristic curve (AUROC) for six different diagnostic labels shows improved performance with increased image resolution and a plateau effect on performance improvement for resolutions higher than 224 × 224 pixels. Models were trained with ResNet34 architecture for three subsample epochs. Resolutions shown are as follows: 32 × 32, 64 × 64, 128 × 128, 224 × 224, 256 × 256, 320 × 320, 448 × 448, 512 × 512, and 600 × 600 pixels. Error bars represent standard deviation of the area under the curve calculated via the DeLong method.