التفاصيل البيبلوغرافية
| العنوان: |
A Robust and Automatic Method for the Best Symmetry Plane Detection of Craniofacial Skeletons |
| المؤلفون: |
Luca Di Angelo, Paolo Di Stefano, Lapo Governi, Antonio Marzola, Yary Volpe |
| المصدر: |
Symmetry; Volume 11; Issue 2; Pages: 245 |
| بيانات النشر: |
Multidisciplinary Digital Publishing Institute |
| سنة النشر: |
2019 |
| المجموعة: |
MDPI Open Access Publishing |
| مصطلحات موضوعية: |
feature recognition, medical imaging, symmetry analysis, mid-sagittal plane, cranio-maxillofacial |
| الوصف: |
The accurate location of the mid-sagittal plane is fundamental for the assessment of craniofacial dysmorphisms and for a proper corrective surgery planning. To date, these elaborations are carried out by skilled operators within specific software environments. Since the whole procedure is based on the manual selection of specific landmarks, it is time-consuming, and the results depend on the operators’ professional experience. This work aims to propose a new automatic and landmark-independent technique which is able to extract a reliable mid-sagittal plane from 3D CT images. The algorithm has been designed to perform a robust evaluation, also in the case of large defect areas. The presented method is an upgraded version of a mirroring-and registration technique for the automatic symmetry plane detection of 3D asymmetrically scanned human faces, previously published by the authors. With respect to the published algorithm, the improvements here introduced concern both the objective function formulation and the method used to minimize it. The automatic method here proposed has been verified in the analysis of real craniofacial skeletons also with large defects, and the results have been compared with other recent technologies. |
| نوع الوثيقة: |
text |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| Relation: |
https://dx.doi.org/10.3390/sym11020245 |
| DOI: |
10.3390/sym11020245 |
| الاتاحة: |
https://doi.org/10.3390/sym11020245 |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ |
| رقم الانضمام: |
edsbas.35D2DEB4 |
| قاعدة البيانات: |
BASE |