A Validation Framework for Head-Motion Artifacts in Dental Cone-Beam CT

Patient motion during CT data acquisition degrades image quality. Therefore, the development of motion detection and motion correction methods are in the focus of many research groups. In general the strength of motion artefacts depends on the motion parameters and on the structures of the anatomical area of interest. Unfortunately, a realistic ground truth data and the corresponding artefact prone reconstructions with known motion parameters during data acquisition are often not available or tedious to obtain. In this work, a framework is presented to generate a database for motion quantification in dental cone-beam CT. Practical aspects and challenges will be described. Furthermore, the generated database will be utilized to investigate the influence of head motion on the reconstruction image quality. Different assessment criteria will be proposed for the motion distorted data. This work provides a basis for data-driven motion detection and correction methods and serves as a first step to understand the effects of motion.