Interventional MRI with sparse sampling using union-of-subspaces

A significant problem in interventional magnetic resonance imaging is limited imaging speed. This paper addresses this problem using a new signal model known as union-of-subspaces. This model enables an effective use of sparse sampling and prior information to significantly improve the imaging speed. The proposed method has been validated using simulations on real interventional imaging data, and is shown to provide high speed and quality imaging. The approach is very flexible and can be applied to other imaging applications as well.