Guiding method and system for daily health care of gingival atrophy patient
A technology of gum recession and guidance system, applied in the field of artificial intelligence, can solve the problems of insufficient knowledge reserve, affecting the recovery effect of patients, weak professionalism, etc., to achieve the effect of improving the quality of recovery
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Embodiment 1
[0024] Such as figure 1 As shown, the embodiment of the present application provides a daily health care guidance method for patients with gingival recession, wherein the method is applied to a daily health care guidance system for patients with gingival recession, and the system is intelligently connected with a camera. The method include:
[0025] Step S100: According to the camera, obtain the first gingiva image information of the first user;
[0026] Specifically, the camera is a miniature smart camera that can penetrate into the oral cavity of the first user to intelligently collect images from multiple angles and distances of the gums. Further, since the multiple image information collected by the camera is For the comprehensive response to the first user’s oral image, it is necessary to further perform quality screening and processing on all the collected image information to obtain the first gingiva image information, wherein, due to the combination of the camera and ...
Embodiment 2
[0085] Based on the same inventive concept as the guidance method for the daily health care of patients with gingival recession in the foregoing embodiments, the present invention also provides a guidance system for daily health care of patients with gingival recession, such as figure 2 As shown, the system includes:
[0086] A first obtaining unit 11, the first obtaining unit 11 is configured to obtain the first gingiva image information of the first user according to the camera;
[0087] A second obtaining unit 12, the second obtaining unit 12 is configured to obtain a first convolutional feature and a second convolutional feature by performing convolutional feature transformation extraction on the first gingival image information;
[0088] The first input unit 13 is configured to input the first convolution feature and the second convolution feature into a first atrophy grade analysis model to obtain a first gingival recession grade;
[0089] A first judging unit 14, the ...
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