Due to a multitude of available image contrasts and the ability to visualize both anatomical and functional information, magnetic resonance imaging (MRI) is well suited for the diagnosis and monitoring of cardiovascular diseases. However, coronary MR imaging is challenging and thus not yet well established in clinical practices. In particular, myocardial contraction and respiratory motion impair MR imaging. 

Methods for iterative image reconstruction enable us to significantly reduce acquisition times while simultaneously avoiding artifacts. The goal of this project is the speedup of an existing iterative reconstruction method for motion- compensated coronary imaging and its generalization to other areas of cardiac imaging, e.g. time-resolved studies, flow or perfusion imaging. 

Based on this prior work, new iterative reconstruction methods with a focus on faster runtimes are to be developed and optimized. Significant speedups should make the algorithms more appealing for use in clinical practices.