Vasculature classification accuracy and 95% CI in the validation dataset were 98.7% ([98.3, 99.1] %) for the best performing model. DLA inference user time was 17 seconds for a throughput of 23 images/s. In conclusion, a 30-layer DLA model outperformed shallower networks and DLA inference computation time was demonstrated not be a limiting factor for current clinical practice.
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Juan C. Montoya, Yinsheng Li, Charles Strother, Guang-Hong Chen, "Deep learning angiography (DLA): three-dimensional C-arm cone beam CT angiography generated from deep learning method using a convolutional neural network," Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 105731N (9 March 2018);