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Bastian Bier M. Sc.

Researcher in the Computed Tomography: Algebraic Reconstruction and Motion (CTARM) group at the Pattern Recognition Lab of the Friedrich-Alexander-Universität Erlangen-Nürnberg

Motion Compensation using Surface Information in CBCT
(Top) Geometry of the acquisition.
(Bottom) Uncorrected and corrected reconstruction.

Cone-beam C-arm CT systems allow to scan patients in weight-bearing positions to assess knee cartilage health under more realistic conditions. Involuntary patient motion during the acquisition results in motion artifacts in the reconstructions. The current motion estimation method is based on fiducial markers. They can be tracked with a high spatial accuracy in the projection images, but only deliver sparse information. Further, placement of the markers on the patient's leg is time consuming and tedious.


Instead of relying on a few well defined points, we seek to establish correspondences on dense surface data to estimate 3D displacements. In this feasibility study, motion corrupted X-ray projections and surface data are simulated. We investigate motion estimation by registration of the surface information.


The proposed approach is compared to a motion free, an uncompensated, and a state-of-the-art marker-based reconstruction using the SSIM. The proposed approach yields motion estimation accuracy and image quality close to the current state-of-the-art, reducing the motion artifacts in the reconstructions remarkably. The Structural Similarity improved from 0.887 to 0.975 from the uncorrected images using the proposed approach. The results are promising and encourage future work aiming at facilitating its practical applicability.




Weight-Bearing C-arm Computed Tomography for the Early Diagnosis of Osteoarthritis
(Left) Acquisition set up in weight-bearing configuration using a C-arm CT.
(Right) Sagittal slice of the reconstructed image of the knee. Thanks to contrast injection, the profile of femural and tibial cartilage is clearly visible.

Osteoarthritis (OA) is the leading cause of functional decline and disability in aging populations. The causes and progression of OA, particularly in the early stages, remain poorly understood. Current OA imaging measures are insensitive to early changes, or are logistically challenging and limited by expense and long scan times. 


The overarching goal of this project is to develop a novel weight-bearing computed tomography (CT) imaging method to expand our understanding of the mechanical stresses that affect cartilage and meniscus health and to provide a quantitative measure of knee joint health. 


Therefore, patients are scanned in standing upright or squatting position. In contrast to acquisitions in supine position, patients are more likely to show involuntary motion which results in motion artifacts in the reconstructions decreasing the diagnostic image quality. Focus of current research is the development of novel motion correction approaches using surface cameras.


More informations about the project can be found Opens external link in new windowhere.


The project is in collaboration with the Opens external link in new windowDepartment of Radiology, Stanford University, Stanford, CA, USA.

Heterogeneous Image Systems

I am a member of the research training group "Heterogeneous Image Systems" Opens external link in new window