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Alexander Preuhs 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

Nature has placed mankind under the governance of two sovereign masters, pain and pleasure. It is for them alone to point out what we ought to do, as well as to determine what we shall do.
Motion Compensation for DynaCT Acquisitions

With modern flat panel C-arm systems, soft tissue imaging is possible during intervention. This can be of high potential in the field of neuroradiologic interventions, when a stroke is to be classified as either ischemic or hemorrhagic. Within the interventional stroke therapy (Mechanical Thrombectomy), DynaCT has the potential to substitute CT and MRT as standard diagnostic modalities. By this substitution, imaging and intervention could be done within one room, making the therapy much faster and thus increasing the quality of stroke therapy.


To reach this goal, the detectability of cerebral bleedings under DynaCT acquisitions must be as reliable as it is using CT. The acquisition of projection data for reconstruction is performed by rotating the C-arm around the patient. One rotation is typically performed in 20 seconds, increasing the risk of motion induced artifacts compared to CT, where a single rotation is performed in less than a second. Thus, a major drawback of DynaCT compared to CT is patient motion. This project aims at compensating motion artifacts in DynaCT acquisitions with the goal of a reliable detectability of cerebral bleedings.

Rigid Motion Creator
Screenshot from motion creator.

A python tool to generate rigid motion is available on Opens external link in new windowGitHub. For bindings to Opens internal link in current windowCONRAD you can find some tutorials here.



Interactive Fan-Beam Reconstruction
Screenshot from the prototype.

An interactive python prototype based on Opens external link in new windowPyConrad for simulating fan-beam projections and fan-beam reconstruction is available on Opens external link in new windowgithub. The reconstruction is performed analytically in a filtered-backprojection scheme.