On the influence of smoothness constraints in computed tomography motion compensation

Thies M, Wagner F, Maul N, Mei S, Gu M, Pfaff L, Vysotskaya N, Yu H, Maier A (2024)


Publication Type: Conference contribution, Original article

Publication year: 2024

Event location: Bamberg

URI: https://www.ct-meeting.org/?p=program

Abstract

Computed tomography (CT) relies on precise patient immobilization during image acquisition. Nevertheless, motion artifacts in the reconstructed images can persist. Motion compensation methods aim to correct such artifacts post-acquisition, often incorporating temporal smoothness constraints on the estimated motion patterns. This study analyzes the influence of a spline-based motion model within an existing rigid motion compensation algorithm for cone-beam CT on the recoverable motion frequencies. Results demonstrate that the choice of motion model crucially influences recoverable frequencies. The optimization-based motion compensation algorithm is able to accurately fit the spline nodes for frequencies almost up to the node-dependent
theoretical limit according to the Nyquist-Shannon theorem. Notably, a higher node count does not compromise reconstruction performance for slow motion patterns, but can extend the range of recoverable high frequencies for the investigated algorithm. Eventually, the optimal motion model is dependent on the imaged anatomy, clinical use case, and scanning protocol and should be tailored carefully to the expected motion frequency spectrum to
ensure accurate motion compensation.

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How to cite

APA:

Thies, M., Wagner, F., Maul, N., Mei, S., Gu, M., Pfaff, L.,... Maier, A. (2024). On the influence of smoothness constraints in computed tomography motion compensation. In Proceedings of the 8th International Conference on Image Formation in X-Ray Computed Tomography (CT Meeting). Bamberg.

MLA:

Thies, Mareike, et al. "On the influence of smoothness constraints in computed tomography motion compensation." Proceedings of the 8th International Conference on Image Formation in X-Ray Computed Tomography (CT Meeting), Bamberg 2024.

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