Abstract
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. Using the proposed method, Structural Similarity improved from 0.887 to 0.975 compared to uncorrected images. The results are promising and encourage future work aiming at facilitating its practical applicability.
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Bier, B. et al. (2017). Motion Compensation Using Range Imaging in C-Arm Cone-Beam CT. In: ValdĂ©s HernĂ¡ndez, M., GonzĂ¡lez-Castro, V. (eds) Medical Image Understanding and Analysis. MIUA 2017. Communications in Computer and Information Science, vol 723. Springer, Cham. https://doi.org/10.1007/978-3-319-60964-5_49
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DOI: https://doi.org/10.1007/978-3-319-60964-5_49
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