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Motion-corrected coronary calcium scores by a CNN: a robotic simulating study
The authors of this study aimed to classify motion-induced blurred images of calcified coronary plaques, in order to correct coronary calcium scored on non-triggered chest computed tomography (CT). They did so by using a deep convolutional neural network (CNN) which was trained using a selection of images of motion artifacts. Key points A deep CNN architecture trained by CT images