Fig. 1: 3D classification workflow. | Nature Communications

Fig. 1: 3D classification workflow.

From: Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets

Fig. 1

All CT images under lung segmentation for localization to chest cavity region. Following cropping to lung region, two methods were considered for differentiation of COVID-19 from other clinical entities. a Full 3D Model resampled the cropped lung region of CT to a fixed size (192 × 192 × 64 voxels) for input to algorithm. b Hybrid CT resampled the cropped lung region of CT to fixed resolution (1mm × 1mm × 5mm) and sampled multiple 3D regions (192 × 192 × 32) for input to algorithm. At training, 6 regions/patient were used. At inference 15 regions/patient were used and results were averaged to produce final probability of COVID-19.

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