1. Automatic Assessment of Calcified Plaque and Nodule by Optical Coherence Tomography Adopting Deep Learning Mode

    Automatic Assessment of Calcified Plaque and Nodule by Optical Coherence Tomography Adopting Deep Learning Mode

    Significance: Detection and characterization of coronary atherosclerotic plaques often need reviews of a large number of optical coherence tomography (OCT) imaging slices to make a clinical decision. However, it is a challenge to manually review all the slices and consider the interrelationship between adjacent slices. Approach : Inspired by the recent success of deep convolutional network on the classification of medical images, we proposed a ResNet-3D network for classification of coronary plaque calcification in OCT pullbacks. The ResNet-3D network was initialized with a trained ResNet-50 network and a three-dimensional convolution filter filled with zeros padding and non-zeros padding with a convolutional ...

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