Acne Severity Grading on Face Images via Extraction and Guidance of Prior Knowledge

Yi Lin, Jingchi Jiang, Dongxin Chen, Zhaoyang Ma, Yi Guan, Xiguang Liu, Haiyan You, Jing Yang, Xue Cheng
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引用次数: 1

Abstract

Acne Vulgaris seriously affects people’s daily life. In this paper, we propose a face acne grading framework which is a new paradigm to solve the image classification problem where the number and type of small objects are the evidence. This framework includes two components: prior knowledge extraction and prior knowledge guided network. The prior knowledge extraction uses an excellent segmentation method to predict the lesion areas as prior knowledge. The prior knowledge guided network fuses the prior knowledge and its corresponding image to grade the severity. The experiment results demonstrate that our framework achieves the state-of-the-art and diagnosis level of dermatologists.
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基于先验知识提取和指导的人脸图像痤疮严重程度分级
寻常痤疮严重影响人们的日常生活。本文提出了一种面部痤疮分级框架,为解决以小目标数量和类型为依据的图像分类问题提供了一种新的范式。该框架包括两个部分:先验知识提取和先验知识引导网络。先验知识提取采用一种优秀的分割方法来预测病变区域作为先验知识。先验知识引导网络将先验知识与其对应的图像进行融合,对严重程度进行分级。实验结果表明,我们的框架达到了皮肤科医生的先进水平和诊断水平。
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