Dalvit Carvalho da Silva Rodrigo, Jenkyn Thomas Richard, Carranza Victor Alexander
Craniofacial Injury and Concussion Research Laboratory, Western University, London, ON N6A 3K7, Canada.
School of Biomedical Engineering, Faculty of Engineering, Western University, London, ON N6A 3K7, Canada.
Biology (Basel). 2021 Mar 2;10(3):182. doi: 10.3390/biology10030182.
In reconstructive craniofacial surgery, the bilateral symmetry of the midplane of the facial skeleton plays an important role in surgical planning. Surgeons can take advantage of the intact side of the face as a template for the malformed side by accurately locating the midplane to assist in the preparation of the surgical procedure. However, despite its importance, the location of the midline is still a subjective procedure. The aim of this study was to present a 3D technique using a convolutional neural network and geometric moments to automatically calculate the craniofacial midline symmetry of the facial skeleton from CT scans. To perform this task, a total of 195 skull images were assessed to validate the proposed technique. In the symmetry planes, the technique was found to be reliable and provided good accuracy. However, further investigations to improve the results of asymmetric images may be carried out.
在颅面重建手术中，面部骨骼中平面的双侧对称性在手术规划中起着重要作用。外科医生可以通过精确确定中平面，利用面部完好的一侧作为畸形侧的模板，以协助手术准备。然而，尽管其很重要，但中线的定位仍然是一个主观过程。本研究的目的是提出一种使用卷积神经网络和几何矩的三维技术，以从CT扫描中自动计算面部骨骼的颅面中线对称性。为完成此任务，共评估了195幅颅骨图像以验证所提出的技术。在对称平面中，该技术被发现是可靠的且具有良好的准确性。然而，可能需要进一步研究以改善不对称图像的结果。
