Loma Linda University
Tooth Length Measurements on 3T MR Images: A Retrospective Study
Abstract
dc:description.abstract<p>Introduction: The purpose of this study was to determine if MRI can be used to accurately measure tooth lengths. Methods: MRI tooth length measurements were compared with “actual tooth lengths” as measured on CBCT scans. Twenty three subjects received two scans (one CBCT and one MRI). Tooth length was measured and compared between the resultant images. Intraclass correlations were used for statistical analysis. Results: Tooth length measurements made on MRI scans showed moderate to almost perfect agreement with tooth length measurements made on CBCT scans. Higher levels of agreement were present in the maxillary arch compared to the mandibular arch. Conclusion: MRI tooth length measurements are similar to CBCT tooth length measurements.</p>
Degree
thesis:*- Name thesis:degree_name
- Master of Science (MS)
- Level thesis:degree_level
- Thesis
- Discipline thesis:degree_discipline
- Orthodontics and Dentofacial Orthopedics
- Year
- 2015
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Murray, Kevin G.
- Contributors dc:contributor
-
- Leggitt, V. Leroy
- Farrage, James
- Neufeld, Roland D.
Subjects
dc:subject × 5- Dentistry
- Medicine and Health Sciences
- Orthodontics and Orthodontology
- Radiography - Dental - Digital; Cone-Beam Computed Tomography; Image Processing - Computer-Assisted; Magnetic Resonance Imaging; Imaging - Three-Dimensional; Retrospective Studies
- Tooth length; MRI tooth length measurements; CBCT scans; Maxillary Arch; Mandibular Arch
Rights
dc:rights- Statement dc:rights
-
- This title appears here courtesy of the author, who has granted Loma Linda University a limited, non-exclusive right to make this publication available to the public. The author retains all other copyrights.
- Language dc:language
- English
Identifiers
dc:identifier.*- Repository record dc:identifier
- https://scholarsrepository.llu.edu/etd/271
- OAI identifier oai:identifier
- oai:scholarsrepository.llu.edu:etd-1272