As people's work pressure gradually increases, more and more people are at risk of getting sick. Doctors use CT images to diagnose the patient's disease. Since there are hundreds of CT images for a complete disease and the key CT images used to illustrate the disease are mainly a few. That is why the problem of image redundancy is highlighted. As a result, the workload of doctors has greatly increased. Therefore, solutions are urgently needed to help quickly identify medical CT images. This paper studies medical image recognition based on convolutional neural networks. Taking dental CT images as an example, the image which is most similar to the key template image is identified through the improved network model of fused feature vectors. Based on this, a platform suitable for all medical CT image recognition has been initially implemented.
Medical Image Recognition Based on Improved Convolutional Neural Network
Lect. Notes Electrical Eng.
International Workshop of Advanced Manufacturing and Automation ; 2020 ; Zhanjiang, China October 12, 2020 - October 13, 2020
2021-01-23
9 pages
Article/Chapter (Book)
Electronic Resource
English
Improved gait recognition based on specialized deep convolutional neural network
British Library Online Contents | 2017
|Vehicle-mounted three-camera image recognition device based on convolutional neural network
European Patent Office | 2021
|