Objective: This study aimed to compare landmark identification errors in anteroposterior (AP) and posteroanterior (PA) cephalograms generated from cone-beam computed tomography (CBCT) scan data in order to examine the feasibility of using AP cephalograms in clinical settings.
Methods: AP and PA cephalograms were generated from CBCT scans obtained from 25 adults. Four experienced and four inexperienced examiners were selected depending on their experience levels in analyzing frontal cephalograms. They identified six cephalometric landmarks on AP and PA cephalograms. The errors incurred in positioning the cephalometric landmarks on the AP and PA cephalograms were calculated by using the straight-line distance and the horizontal and vertical components as parameters.
Results: Comparison of the landmark identification errors in CBCT-generated frontal cephalograms revealed that landmark-dependent differences were greater than experience- or projection-dependent differences. Comparisons of landmark identification errors in the horizontal and vertical directions revealed larger errors in identification of the crista galli and anterior nasal spine in the vertical direction and the menton in the horizontal direction, in comparison with the other landmarks. Comparison of landmark identification errors between the AP and PA projections in CBCT-generated images revealed a slightly higher error rate in the AP projections, with no inter-examiner differences. Statistical testing of the differences in landmark identification errors between AP and PA cephalograms showed no statistically significant differences for all landmarks.
Conclusions: The reproducibility of CBCT-generated AP cephalograms is comparable to that of PA cephalograms; therefore, AP cephalograms can be generated reliably from CBCT scan data in clinical settings.
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http://dx.doi.org/10.4041/kjod.2019.49.1.41 | DOI Listing |
Sci Rep
January 2025
School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran.
Anatomical Landmark detection in CT-Scan images is widely used in the identification of skeletal disorders. However, the traditional process of manually detecting anatomical landmarks, especially in three dimensions, is both time-consuming and prone to human errors. We propose a novel, deep-learning-based approach to automatic detection of 3D landmarks in CT images of the lower limb.
View Article and Find Full Text PDFSci Rep
January 2025
Division in Anatomy and Developmental Biology, Department of Oral Biology, Human Identification Research Institute, BK21 FOUR Project, Yonsei University College of Dentistry, Seoul, 03722, Republic of Korea.
Computational analysis of the pubic symphyseal surface is widely used for accurate age estimation, offering quantitative precision through the detection of subtle morphological changes. However, these methods often lack insights into the underlying morphological changes across different age groups. To bridge this gap, the study utilizes statistical shape modeling (SSM), a versatile tool capable of describing diverse morphological variations within populations.
View Article and Find Full Text PDFBMC Pregnancy Childbirth
December 2024
Department of Anesthesiology, West China Second University Hospital, Sichuan University, 20#, Section 3 Renmin Nan Road, Chengdu, Sichuan, 610041, PR China.
Background: While the line joining the posterior superior iliac spine (PSIS) intersects a relatively stable sacral vertebra, it does not directly facilitate the localization of lumbar interspace or assist in the positioning for neuraxial anesthesia. Our study aimed to explore the potential of the PSIS line as a reference point and to determine its practical applicability in clinical settings.
Methods: We consecutively enrolled pregnant women with gestational ages ranging from 24 to 38 weeks scheduled for magnetic resonance imaging (MRI) examination.
Subcell Biochem
December 2024
ALBA Synchrotron Light Source, Cerdanyola del Vallès, Spain.
Since the 1970s and for about 40 years, X-ray crystallography has been by far the most powerful approach for determining virus structures at close to atomic resolutions. Information provided by these studies has deeply and extensively enriched and shaped our vision of the virus world. In turn, the ever-increasing complexity and size of the virus structures being investigated have constituted a major driving force for methodological and conceptual developments in X-ray macromolecular crystallography (MX).
View Article and Find Full Text PDFFront Biosci (Landmark Ed)
November 2024
Department of Orthopaedics, The Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, 646000 Luzhou, Sichuan, China.
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