Rose acne classification software based on computer vision

Abstract

The invention discloses acnes rosacea identification and classification software based on computer vision. The acnes rosacea identification and classification software comprises a mobile terminal image acquisition system, an acnes rosacea category data system, an acnes rosacea category judgment system and a personalized user upgrading system, the mobile end image acquisition system is used for acquiring facial rosacea disease images through a photographing function of a mobile end; the rosacea category data system can utilize a deep learning mode to carry out high-intensity learning and training on rosacea category data; the acne rosacea category judgment system obtains a category result from the facial acne rosacea picture of the patient according to a learning model matching result; according to the personalized user upgrading system, the category of the rosacea disease can be newly increased according to the characteristics of the patient, so that the accuracy of rosacea classification is ensured. According to the invention, simultaneous classification and identification of different types of rosacea can be completed through simple shooting operation, and convenience is provided for clinical diagnosis of doctors.

Description

technical field [0001] The invention relates to a computer vision technology, in particular to a rosacea category recognition software based on computer vision. [0002] technical background [0003] Rosacea is a chronic inflammatory skin disease that occurs in the middle of the face. It is common in females aged 20 to 70. The number of female patients is much higher than that of male patients, and the elderly and children also have a higher prevalence of rosacea. disease risk. Although there are many studies on the prevalence and risk groups of rosacea, there are significant differences in the results of these studies. The differences in research results are likely to be related to factors such as different research methods, inconsistent diagnostic criteria, different dietary and living habits, genetic or ethnic differences, and different regional climates, but from a global perspective, the overall prevalence of rosacea in different populations The rate is increasing year...

AI Technical Summary

Problems solved by technology

According to relevant surveys, the number of patients with rosacea continues to increase every year, and the number of dermatologists is seriously insufficient, which leads to overloaded work of dermatologists, which greatly reduces the accuracy and efficiency of dermatologists in diagnosing rosacea. Therefore, A new technical approach is urgently needed to assist dermatologists in the rapid and accurate diagnosis of rosacea

There is a large amount of redundant data generation in traditional medicine, which leads to the problem of low learning efficiency, and manual feature extraction is difficult to capture advanced semantic features and complex content

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