Abstract
At present, in medical diagnosis, facial acne vulgaris is a common disease, which mainly occurs in adolescents and has a large population base. For different degrees of facial acne, it needs to be classified and treated to relieve the pressure on medical resources. Normally, dermatologists use models that artificially determine the severity of acne vulgaris on the face. However, the outstanding problem is that it is a waste of manpower, and it may not be possible to quickly and reasonably grade acne treatment of different degrees. In this article, in view of the above problems, image recognition is used to judge the severity of facial acne vulgaris at different levels, so that perform hierarchical diagnosis and treatment. Therefore, this paper designs a graded diagnosis and treatment system for facial acne vulgaris based on image recognition. The system includes a camera acquisition system, an image processing system, an image recognition system, and related detection algorithms. In the processing process, the collected facial acne vulgaris images are mainly subjected to color processing, image segmentation processing and contour detection, and combined with Harris corner detection algorithm to detect acne. In order to determine the severity of acne and the site of the disease to a certain extent, and provide a reference for graded diagnosis and treatment.
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The study was supported by Key projects of national key research and development plan (2017YFF0207400): Research on key technologies and important standards of health services and remote health monitoring for the elderly and the disabled.
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Chen, L., Li, Y., Han, L., Yuan, L., Sun, Y., Tang, X. (2020). Classification and Treatment System for Facial Acne Vulgaris Based on Image Recognition. In: Elderly Health Services and Remote Health Monitoring. SpringerBriefs in Applied Sciences and Technology. Springer, Singapore. https://doi.org/10.1007/978-981-15-7154-1_6
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DOI: https://doi.org/10.1007/978-981-15-7154-1_6
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