Department of Preventive Dentistry, University of Medicine and Pharmacy Iuliu Hatieganu, Cluj-Napoca, Romania Chifor Research SRL, Cluj-Napoca, Romania.
Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB, Canada Department of Implantology, School and Hospital of Stomatology, Wuhan University, Wuhan, China.
Med Ultrason. 2021 Aug 11;23(3):297-304. doi: 10.11152/mu-2837. Epub 2021 Mar 3.
To demonstrate the feasibility of the 3D ultrasound periodontal tissue reconstruction of the lateral area of a porcine mandible using standard 2D ultrasound equipment and spatial positioning reading sensors.
Periodontal 3D reconstructions were performed using a free-hand prototype based on a 2D US scanner and a spatial positioning reading sensor. For automated data processing, deep learning algorithms were implemented and trained using semi-automatically seg-mented images by highly specialized imaging professionals.
US probe movement analysis showed that non-parallel 2D frames were acquired during the scanning procedure. Comparing 3 different 3D periodontal reconstructions of the same porcine mandible, the accuracy ranged between 0.179 mm and 0.235 mm.
The present study demonstrated the diagnostic potential of 3D reconstruction using a free-hand 2D US scanner with spatial positioning readings. The use of auto-mated data processing with deep learning algorithms makes the process practical in the clinical environment for assessment of periodontal soft tissues.
展示使用标准二维超声设备和空间定位读取传感器对猪下颌侧方牙周组织进行三维超声重建的可行性。
基于二维超声扫描仪和空间定位读取传感器,使用自由手原型进行牙周三维重建。为了实现自动化数据处理,使用由专业影像医师半自动分割的图像对深度学习算法进行了实现和训练。
超声探头运动分析显示,在扫描过程中采集了非平行的二维帧。比较同一头猪下颌的 3 种不同的牙周三维重建,精度在 0.179 毫米至 0.235 毫米之间。
本研究证明了使用带有空间定位读数的自由手二维超声扫描仪进行三维重建的诊断潜力。使用具有深度学习算法的自动化数据处理使得该过程在临床环境中评估牙周软组织成为可能。