we combine the model output into the original CT volume. The 3D CNN was trained using the SGD optimizer with a momentum of 0.9, a peak learning rate of 0.1 for randomly initialized weights, a weight decay of 0.
To compare radiology residents’ diagnostic performances to detect pulmonary emboli (PEs) on CT pulmonary angiographies (CTPAs) with deep-learning (DL)–based algorithm support and without. Methods Fully anonymized CTPAs (n = 207) of patients suspected of having acute PE served as input for PE...