Faculty of Engineering, Chiang Mai University, Chiang Mai, Thailand.
Intercountry Centre for Oral Health, Ministry of Public Health, Chiang Mai, Thailand.
Stud Health Technol Inform. 2024 Aug 22;316:1096-1097. doi: 10.3233/SHTI240601.
Dentists, especially those who are not oral lesion specialists and live in rural areas, need an artificial intelligence (AI) system for accurately assisting them in screening for oral cancer that may appear in smartphone images. Not many literatures present a viable model that addresses the needs, especially in the context of oral lesion segmentation in smartphone images. This study demonstrates the use of a deep learning-based AI for simultaneously identifying types of oral cancer lesions as well as precisely outlining the boundary of the lesions in the images for the first time. The lesions of interest were oral potentially malignant disorders (OPMDs) and oral squamous cell carcinoma (OSCC) lesions. The model could successfully (1) detect if the images contained the oral lesions, (2) determine types of the lesions, and (3) precisely outline the boundary of the lesions. With future success of our project, patients will be diagnosed and treated early before the pre-cancer lesions can progress into deadly cancerous ones.
牙医,特别是那些非口腔病变专家且居住在农村地区的牙医,需要一个人工智能(AI)系统来帮助他们准确筛查可能出现在智能手机图像中的口腔癌。目前还没有很多文献提出可行的模型来满足这一需求,特别是在智能手机图像中口腔病变分割的背景下。本研究首次展示了一种基于深度学习的 AI 用于同时识别口腔癌病变类型以及精确勾勒图像中病变边界的应用。所关注的病变包括口腔潜在恶性疾病(OPMDs)和口腔鳞状细胞癌(OSCC)病变。该模型能够成功地(1)检测图像中是否包含口腔病变,(2)确定病变类型,以及(3)精确勾勒病变边界。如果我们的项目取得成功,患者将在癌前病变进展为致命的癌症之前得到早期诊断和治疗。