Abhishek Gupta1,2, Om Prakash Kharbanda3, Viren Sardana2, Rajiv Balachandran3, Harish Kumar Sardana4,5. 1. Academy of Scientific & Innovative Research (AcSIR), New Delhi, India. 2. CSIR-Central Scientific Instruments Organisation, Chandigarh, 160030, India. 3. Centre for Dental Education and Research, All India Institute of Medical Sciences, New Delhi, 110029, India. 4. Academy of Scientific & Innovative Research (AcSIR), New Delhi, India. hk_sardana@csio.res.in. 5. CSIR-Central Scientific Instruments Organisation, Chandigarh, 160030, India. hk_sardana@csio.res.in.
Abstract
PURPOSE: To evaluate the accuracy of three-dimensional cephalometric measurements obtained through an automatic landmark detection algorithm compared to those obtained through manual identification. METHODS: The study demonstrates a comparison of 51 cephalometric measurements (28 linear, 16 angles and 7 ratios) on 30 CBCT (cone beam computed tomography) images. The analysis was performed to compare measurements based on 21 cephalometric landmarks detected automatically and those identified manually by three observers. RESULTS: Inter-observer ICC for each landmark was found to be excellent ([Formula: see text]) among three observers. The unpaired t-test revealed that there was no statistically significant difference in the measurements based on automatically detected and manually identified landmarks. The difference between the manual and automatic observation for each measurement was reported as an error. The highest mean error in the linear and angular measurements was found to be 2.63 mm ([Formula: see text] distance) and [Formula: see text] ([Formula: see text]-Me angle), respectively. The highest mean error in the group of distance ratios was 0.03 (for N-Me/N-ANS and [Formula: see text]). CONCLUSION: Cephalometric measurements computed from automatic detection of landmarks on 3D CBCT image were as accurate as those computed from manual identification.
PURPOSE: To evaluate the accuracy of three-dimensional cephalometric measurements obtained through an automatic landmark detection algorithm compared to those obtained through manual identification. METHODS: The study demonstrates a comparison of 51 cephalometric measurements (28 linear, 16 angles and 7 ratios) on 30 CBCT (cone beam computed tomography) images. The analysis was performed to compare measurements based on 21 cephalometric landmarks detected automatically and those identified manually by three observers. RESULTS: Inter-observer ICC for each landmark was found to be excellent ([Formula: see text]) among three observers. The unpaired t-test revealed that there was no statistically significant difference in the measurements based on automatically detected and manually identified landmarks. The difference between the manual and automatic observation for each measurement was reported as an error. The highest mean error in the linear and angular measurements was found to be 2.63 mm ([Formula: see text] distance) and [Formula: see text] ([Formula: see text]-Me angle), respectively. The highest mean error in the group of distance ratios was 0.03 (for N-Me/N-ANS and [Formula: see text]). CONCLUSION: Cephalometric measurements computed from automatic detection of landmarks on 3D CBCT image were as accurate as those computed from manual identification.
Entities:
Keywords:
3D cephalometry; Automatic landmarking; CBCT; Cephalometric analysis; Knowledge-based detection
Authors: Manuel O Lagravère; Jillian M Gordon; Ines H Guedes; Carlos Flores-Mir; Jason P Carey; Giseon Heo; Paul W Major Journal: Angle Orthod Date: 2009-11 Impact factor: 2.079
Authors: Najla Al Turkestani; Jonas Bianchi; Romain Deleat-Besson; Celia Le; Li Tengfei; Juan Carlos Prieto; Marcela Gurgel; Antonio C O Ruellas; Camila Massaro; Aron Aliaga Del Castillo; Karine Evangelista; Marilia Yatabe; Erika Benavides; Fabiana Soki; Winston Zhang; Kayvan Najarian; Jonathan Gryak; Martin Styner; Jean-Christophe Fillion-Robin; Beatriz Paniagua; Reza Soroushmehr; Lucia H S Cevidanes Journal: Orthod Craniofac Res Date: 2021-05-24 Impact factor: 1.826
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