Objective: To locate CT images by using the deep learning model based on convolutional neural network.
Methods: The AlexNet network was used as a deep learning model, which was preset by the transfer learning approach. Training samples were divided into 4 categories according to the vertebral body parts and labeled, and the data augmentation was used to improve the classification accuracy.
Results: The accuracy of image classification after augmentation increased from 94.95% to 97.72%, and the testing time increased from 2.05 s to 3.03 s.
Conclusions: It is feasible to use the convolutional neural network to locate CT images. The data augmentation approach can increase the classification accuracy but also increase the training and testing time.
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| http://dx.doi.org/10.3969/j.issn.1671-7104.2019.06.017 | DOI Listing |
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