后牙窝沟龋深度学习分割模型的建立  

A deep learning segmentation model for detecting caries in molar teeth

作　　者：臧小漪 乔波 孟凡皓 靳能皓 胡随馨 李粮博 邢乐君[1] 陈飞[1] 王懿[1] 张海钟[1] Zang Xiaoyi;Qiao Bo;Meng Fanhao;Jin Nenghao;Hu Suixin;Li Liangbo;Xing Lejun;Chen Fei;Wang Yi;Zhang Haizhong(Department of Stomatology,the First Medical Center of Chinese PLA General Hospital,Beijing 100853,China)

机构地区：[1]解放军总医院第一医学中心口腔科解放军医学院,北京100853

出　　处：《中华医学杂志》2022年第32期2538-2540,共3页National Medical Journal of China

摘　　要：本研究目的是建立一个可家用的能直接显示龋病范围的深度学习分割模型。收集解放军总医院第一医学中心口腔科门诊2019年9月至2021年6月共494张用内窥镜采集的、含有龋齿的磨牙和前磨牙照片,由医师进行标注后用DeepLabv3+进行分割训练,随后进行验证和评估。建立的深度学习分割模型识别龋病的平均准确度为0.993,灵敏度为0.661,特异度为0.997,Dice系数为0.685,并交比(IoU)为0.529。本研究建立的深度学习分割模型可以识别并分割出龋病范围。This study aimed to build a home use deep learning segmentation model to identify the scope of caries lesions.A total of 494 caries photographs of molars and premolars collected via endoscopy were selected.Subsequently,these photographs were labeled by physicians and underwent segmentation training by using DeepLabv3+,and then verification and evaluation were performed.The mean accuracy was 0.993,the sensitivity was 0.661,the specificity was 0.997,the Dice coefficient was 0.685,and the intersection over union(IoU)was 0.529.Therefore,the present deep learning segmentation model can identify and segment the scope of caries.

关 键 词：龋齿 内窥镜 深度学习 图像分割 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TP18[自动化与计算机技术—计算机科学与技术] R781.1[医药卫生—口腔医学]