Buyukcavus Muhammed Hilmi, Aydogan Akgun Filiz, Solak Serdar, Ucar Mustafa Hikmet Bilgehan, Fındık Yavuz, Baykul Timucin
Faculty of Dentistry, Department of Orthodontics, Antalya Bilim University, Antalya, Turkey.
Faculty of Dentistry, Department of Orthodontics, Burdur Mehmet Akif Ersoy University, Burdur, Turkey.
J Orofac Orthop. 2025 Mar;86(2):98-107. doi: 10.1007/s00056-023-00494-y. Epub 2023 Sep 29.
This study aimed to investigate whether the facial soft tissue changes of individuals who had undergone surgically assisted rapid maxillary expansion (SARME) would be detected by three different well-known facial biometric recognition applications.
To calculate similarity scores, the pre- and postsurgical photographs of 22 patients who had undergone SARME treatment were examined using three prominent cloud computing-based facial recognition application programming interfaces (APIs): AWS Rekognition (Amazon Web Services, Seattle, WA, USA), Microsoft Azure Cognitive (Microsoft, Redmond, WA, USA), and Face++ (Megvii, Beijing, China). The pre- and post-SARME photographs of the patients (relaxed, smiling, profile, and semiprofile) were used to calculate similarity scores using the APIs. Friedman's two-way analysis of variance and the Wilcoxon signed-rank test were used to compare the similarity scores obtained from the photographs of the different aspects of the face before and after surgery using the different programs. The relationship between measurements on lateral and posteroanterior cephalograms and the similarity scores was evaluated using the Spearman rank correlation.
The similarity scores were found to be lower with the Face++ program. When looking at the photo types, it was observed that the similarity scores were higher in the smiling photos. A statistically significant difference in the similarity scores (P < 0.05) was found between the relaxed and smiling photographs using the different programs. The correlation between the cephalometric and posteroanterior measurements and the similarity scores was not significant (P > 0.05).
SARME treatment caused a significant change in the similarity scores calculated with the help of three different facial recognition programs. The highest similarity scores were found in the smiling photographs, whereas the lowest scores were found in the profile photographs.
本研究旨在调查三种不同的知名面部生物识别应用程序能否检测出接受外科辅助快速上颌扩展(SARME)治疗的个体面部软组织的变化。
为了计算相似度得分,使用三个基于云计算的著名面部识别应用程序编程接口(API)对22例接受SARME治疗的患者的术前和术后照片进行了检查:AWS Rekognition(美国华盛顿州西雅图市亚马逊网络服务公司)、Microsoft Azure Cognitive(美国华盛顿州雷德蒙德市微软公司)和Face++(中国北京旷视科技有限公司)。使用这些API,利用患者的术前和术后照片(放松状态、微笑状态、侧面和半侧面)来计算相似度得分。采用弗里德曼双向方差分析和威尔科克森符号秩检验,比较使用不同程序获得的手术前后面部不同部位照片的相似度得分。使用斯皮尔曼等级相关性评估侧位和后前位头影测量值与相似度得分之间的关系。
发现Face++程序的相似度得分较低。在查看照片类型时,观察到微笑照片中的相似度得分较高。使用不同程序时,放松照片和微笑照片之间的相似度得分存在统计学显著差异(P<0.05)。头影测量值和后前位测量值与相似度得分之间的相关性不显著(P>0.05)。
SARME治疗导致在三种不同面部识别程序帮助下计算出的相似度得分发生了显著变化。微笑照片中的相似度得分最高,而侧面照片中的得分最低。