摘要： 目的: 基于卷積神經(jīng)網(wǎng)絡(luò)(convolutional neural network,CNN)的深度學習技術(shù)構(gòu)建人工智能(artificial intelligence,AI)牙周病早篩模型,輔助非牙周醫(yī)生對牙周病進行早期篩查。方法: 收集南昌大學第二附屬醫(yī)院口腔醫(yī)學診療中心就診的牙周非健康人群以及牙周健康人群的口內(nèi)數(shù)碼照和臨床資料?；赩GG-16結(jié)構(gòu)對口內(nèi)數(shù)碼照圖像進行訓(xùn)練和測試,建立口腔九宮格、正位咬合、正位咬合(剔除無效背景)3種訓(xùn)練集模型。結(jié)果: 共收集到578位研究對象的3869張口內(nèi)數(shù)碼照圖像,其中牙周健康圖像2230張,牙周非健康圖像1639張。采用VGG-16結(jié)構(gòu)建立3種訓(xùn)練集模型,對九宮格口內(nèi)數(shù)碼照、正位咬合口內(nèi)數(shù)碼照、正位咬合(剔除無效背景)口內(nèi)數(shù)碼照預(yù)測的準確度分別為66.62%、64.66%、77.44%,曲線下面積(area under curve,AUC)值分別為0.651、0.767、0.784。結(jié)論: 本研究構(gòu)建的VGG-16模型能有效通過對口內(nèi)數(shù)碼照圖像識別,輔助非牙周醫(yī)生對牙周病進行早篩。

關(guān)鍵詞: 卷積神經(jīng)網(wǎng)絡(luò), 牙周病, 深度學習, 人工智能

Abstract: Objective: To construct an artificial intelligence (AI) early screening model of periodontal disease based on convolutional neural network (CNN) deep learning technology, and to assist non-periodontal doctors in early screening of periodontal disease. Methods: The oral digital photos and clinical data of periodontal non-healthy people and periodontal healthy people were collected from the Second Affiliated Hospital of Nanchang University. Vgg-16 was used to train and test intra oral digital images. Three training models, i.e. nine grid mouth, orthotopic occlusal, and orthotopic occlusal excluding invalid background, were established. Results: A total of 3869 oral digital images of 578 subjects were collected, including 2230 periodontal healthy images and 1639 periodontal unhealthy images. Vgg-16 was used to establish three kinds of training set models. The accuracy of prediction of digital image in nine grid mouth, digital image in orthotopic occlusal mouth, and digital image in orthotopic occlusal mouth excluding invalid background were 66.62%, 64.66%, and 77.44%, respectively. AUC values were 0.651, 0.767, and 0.784, respectively. Conclusion: The VGG-16 model constructed in this study can effectively assist non-periodontal doctors in early screening of periodontal disease through intra-oral digital image recognition.

Key words: convolutional neural network, periodontal disease, deep learning, artificial intelligence

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