摘要
目的舌图像分割是舌诊客观化的关键之一,易受舌体附近嘴唇和皮肤等带来的影响,而增加分割的难度。针对该问题,为确保舌图像分割的准确性,本研究提出一种基于卷积神经网络Mask R-CNN的舌图像分割方法。方法首先用标注工具labelme对舌图像进行标注,然后进行Mask R-CNN舌图像分割模型的训练和舌图像分割测试。结果采用该方法进行舌图像分割,获得的舌体边缘比较准确,并且四个定量评价指标均像素准确度、平均准确度、均交并比、频权交并比均高于84.6%。结论本研究取得了较好的舌体分割效果,能够改善舌体周围的嘴唇和皮肤颜色与舌体颜色接近导致舌体分割轮廓不准确的问题,为舌图像分割提供了一种新的思路与方法,对舌诊客观化具有一定实用价值和借鉴意义。
Tongue image segmentation is one of the keys to the objectification of tongue diagnosis.When the color of the tongue is close to the lips or the skin,it will have a greater influence on the segmentation of tongue.This increases the difficulty of segmentation.Therefore,this paper proposed a tongue image segmentation method based on Mask R-CNN of convolutional neural network.In order to improve the accuracy of tongue image segmentation,firstly,the tongue image is labeled with the labeling tool labelme,and then the tongue image segmentation model of Mask R-CNN is trained and the test of tongue image segmentation is carried out.The tongue segmentation edge obtained by the tongue image segmentation method is more accurate.And the four quantitative evaluation indexes of the method are higher than 84.6%,which are Mean Pixel Accuracy,Mean Accuracy,Mean Intersection over Union and Mean Frequency Weighted Intersection over Union.This method achieves better tongue segmentation effect.It can solve the problem of inaccurate segmentation of the tongue image caused by the color of the lips and skin being closer to that of the tongue.This research provides a new idea and method for tongue image segmentation,which has certain practical value and reference significance for the objectification of tongue diagnosis.
作者
颜建军
徐姿
郭睿
燕海霞
王忆勤
Yan Jianjun;Xu Zi;Guo Rui;Yan Haixia;Wang Yiqin(School of Mechanical and Power Engineering,East China University of Science and Technology,Shanghai 200237,China;Institute of Interdisciplinary Research Complex,Shanghai University of Traditional Chinese Medicine,Shanghai 201203,China;Laboratory of Information Access and Synthesis of Traditional Chinese Medicine Four Diagnosis,Shanghai University of Traditional Chinese Medicine,Shanghai 201203,China)
出处
《世界科学技术-中医药现代化》
CSCD
北大核心
2020年第5期1532-1538,共7页
Modernization of Traditional Chinese Medicine and Materia Medica-World Science and Technology
基金
国家自然科学基金委员会面上项目(81673880):基于中医四诊大数据的冠心病风险评估与预测模型研究
负责人:王忆勤
关键词
舌图像分割
舌诊客观化
卷积神经网络
实例分割
深度学习
Tongue Image Segmentation
Tongue Diagnosis Objectification
Convolutional Neural Network
Image Annotation
Deep Learning
作者简介
通讯作者:王忆勤,教授,本刊编委,主要研究方向:中医诊断规范化、标准化研究;通讯作者:郭睿,副研究员,主要研究方向:中医四诊客观化。
