Model-based reconstruction methods for CT perfusion imaging
M1.1b | Dynamic C-arm CT perfusion of the liver
In general, dynamic perfusion imaging using C-arm devices is a challenging task, particularly owing to the slow rotation speed of such devices, which results in temporally undersampled data. Recent advances in so-called model-based reconstruction algorithms (e.g. Bannasch et al.) have demonstrated great potential in the field of brain perfusion. While dynamic perfusion imaging is quite established for imaging the human brain, liver perfusion is not part of the clinical routine yet. This can be attributed to the insufficient image quality that is provided by conventional algorithms when applied to liver imaging without appropriate modifications.
Consequenly, the main objective of this project is to solve this by adapting existing routines from brain perfusion to the specific liver requirements and by adding necessary components that address central issues of the problem, like ...
- consideration of strong patient movement (especially due to breathing),
- dealing with severe truncation in the acquired projections (limited field of view), as well as
- handling the extensive computational load of the image reconstruction
thereby aiming at the
- development of suitable image reconstruction algorithms,
- integration of prior knowledge about involved processes, and
- (fast) implementation of all developed routines
to enable the assessment of perfusion parameters in the (human) liver.
Sub-project kickoff: tba.