Parallel imaging with prior information for dynamic MRI

Many imaging applications require collecting a time series of images with similar backgrounds. Conventional MRI methods acquire these images independently, leading to a trade-off between spatial and temporal resolution. To address this problem, this paper presents a novel algorithm to integrate prior-information driven imaging with parallel imaging using multiple receiver coils. In this work, two novel techniques, reconstruction with prior information for dynamic MRI (RPID) and linear interpolation in K-space (LIKE) are combined for application to dynamic MRI. With one fully sampled K-space pre-scan, the required K-space data for all other images can be dramatically reduced by applying the proposed method. The reduction factor may be larger than the number of channels without much loss of information. Experimental results from contrast enhanced MRI studies demonstrate that the proposed algorithm can produce high quality dynamic images with large acceleration factors.