Jesús Montúfar1, Marcelo Romero2, Rogelio J Scougall-Vilchis3. 1. Department of Engineering, Universidad Autónoma del Estado de México, Toluca, Mexico. 2. Department of Engineering, Universidad Autónoma del Estado de México, Toluca, Mexico. Electronic address: mromeroh@uaemex.mx. 3. Department of Odontology, Universidad Autónoma del Estado de México, Toluca, Mexico.
Abstract
INTRODUCTION: This article presents a novel technique for automatic cephalometric landmark localization on 3-dimensional (3D) cone-beam computed tomography (CBCT) volumes by using an active shape model to search for landmarks in related projections. METHODS: Twenty-four random CBCT scans from a public data set were imported and processed into Matlab (MathWorks, Natick, Mass). Orthogonal coronal and sagittal projections (digitally reconstructed radiographs) were created, and 2 trained active shape models were used to locate cephalometric landmarks on each. Finally, by relating projections, 18 tridimensional landmarks were located on CBCT volume representations. RESULTS: From our 3D gold standard, a 3.64-mm mean error in localization of cephalometric landmarks was achieved with this method, with the highest localization errors in the porion and sella regions because of the low volume definition. CONCLUSIONS: The proposed algorithm for automatic 3D landmarking on CBCT volumes seems to be useful for 3D cephalometric analysis. This study shows that a fast 2-dimensional landmark search can be useful for 3D localization, which could save computational time compared with a full-volume analysis. Also, this research confirms that by using CBCT for cephalometry, there are no distortion projections, and full structure information of a virtual patient is manageable in a personal computer.
INTRODUCTION: This article presents a novel technique for automatic cephalometric landmark localization on 3-dimensional (3D) cone-beam computed tomography (CBCT) volumes by using an active shape model to search for landmarks in related projections. METHODS: Twenty-four random CBCT scans from a public data set were imported and processed into Matlab (MathWorks, Natick, Mass). Orthogonal coronal and sagittal projections (digitally reconstructed radiographs) were created, and 2 trained active shape models were used to locate cephalometric landmarks on each. Finally, by relating projections, 18 tridimensional landmarks were located on CBCT volume representations. RESULTS: From our 3D gold standard, a 3.64-mm mean error in localization of cephalometric landmarks was achieved with this method, with the highest localization errors in the porion and sella regions because of the low volume definition. CONCLUSIONS: The proposed algorithm for automatic 3D landmarking on CBCT volumes seems to be useful for 3D cephalometric analysis. This study shows that a fast 2-dimensional landmark search can be useful for 3D localization, which could save computational time compared with a full-volume analysis. Also, this research confirms that by using CBCT for cephalometry, there are no distortion projections, and full structure information of a virtual patient is manageable in a personal computer.
Authors: Julie D White; Alejandra Ortega-Castrillón; Harold Matthews; Arslan A Zaidi; Omid Ekrami; Jonatan Snyders; Yi Fan; Tony Penington; Stefan Van Dongen; Mark D Shriver; Peter Claes Journal: Sci Rep Date: 2019-04-15 Impact factor: 4.379
Authors: Yashodhan M Bichu; Ismaeel Hansa; Aditi Y Bichu; Pratik Premjani; Carlos Flores-Mir; Nikhilesh R Vaid Journal: Prog Orthod Date: 2021-07-05 Impact factor: 2.750