A deep learning model using convolutional neural networks for caries detection and recognition with endoscopes

doi:10.21037/atm-22-5816

	A deep learning model using convolutional neural networks for caries detection and recognition with endoscopes
	Zang, Xiaoyi 1,2; Luo, Chunlong 3,4; Qiao, Bo 1,2; Jin, Nenghao 1,2; Zhao, Yi 3; Zhang, Haizhong 2,5
	2022-12-19
发表期刊	ANNALS OF TRANSLATIONAL MEDICINE
ISSN	2305-5839
页码	11
摘要	Background: Caries are common, especially in economically undeveloped countries with limited access to medical resources. Sometimes patient cannot even realize that they have oral problems until they feel obvious pain. Deep convolutional neural networks (CNNs) have been widely adopted for medical image analysis and management and have yielded some progress in stomatology while the endoscopes are cheap and easily used in daily life for families or other non-medical situations. Therefore, we created a deep learning model to detect and recognize caries using endoscopic images. Methods: We used 194 images of non-caries and 1,059 images of permanent molar and premolar caries to build a classification and a segmentation model in patients of endoscope images from the Department of Stomatology of People's Liberation Army General Hospital (PLAGH). A classification model combined with an end-to-end semantic segmentation model, DeepLabv3+ was used for segmenting the caries, then we evaluated with a 5-fold cross-validation protocol whereby each fold was used once. Results: In the classification model, the mean area under the curve (AUC) [90% confidence interval (CI)] was 0.9897 (0.9821-0.9956) (P<0.01) In the segmentation model, the mean accuracy was 0.9843 (0.9820-0.9871), the recall was 0.6996 (0.6810-0.7194), the specificity was 0.9943 (0.9937-0.9954), the Dice coefficient was 0.7099 (0.6948-0.7343), and the intersection over union (IoU) was 0.5779 (0.5646-0.6006). Conclusions: We used a deep learning model to monitor caries and encourage their early diagnosis and treatment.
关键词	Artificial intelligence (AI) caries lesions endoscopes deep learning
DOI	10.21037/atm-22-5816
收录类别	SCI
语种	英语
资助项目	National Key R&D Program of China ; [2020YFC2008900]
WOS研究方向	Oncology ; Research & Experimental Medicine
WOS类目	Oncology ; Medicine, Research & Experimental
WOS记录号	WOS:000905672900001
出版者	AME PUBLISHING COMPANY
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/20144
专题	中国科学院计算技术研究所期刊论文
通讯作者	Zhang, Haizhong
作者单位	1.Med Sch Chinese PLA, Beijing, Peoples R China 2.Chinese Peoples Liberat Army Gen Hosp, Med Ctr 1, Dept Stomatol, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Res Ctr Ubiquitous Comp Syst, Beijing, Peoples R China 4.Univ Chinese Acad Sci, Beijing, Peoples R China 5.Chinese Peoples Liberat Army Gen Hosp, Med Ctr 1, Dept Stomatol, 28 Fuxing Rd, Beijing 100853, Peoples R China
推荐引用方式 GB/T 7714	Zang, Xiaoyi,Luo, Chunlong,Qiao, Bo,et al. A deep learning model using convolutional neural networks for caries detection and recognition with endoscopes[J]. ANNALS OF TRANSLATIONAL MEDICINE,2022:11.
APA	Zang, Xiaoyi,Luo, Chunlong,Qiao, Bo,Jin, Nenghao,Zhao, Yi,&Zhang, Haizhong.(2022).A deep learning model using convolutional neural networks for caries detection and recognition with endoscopes.ANNALS OF TRANSLATIONAL MEDICINE,11.
MLA	Zang, Xiaoyi,et al."A deep learning model using convolutional neural networks for caries detection and recognition with endoscopes".ANNALS OF TRANSLATIONAL MEDICINE (2022):11.