Feasibility Study on Location of CT Images Using Convolutional Neural Networks

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. Conclusion 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.