title: A computationally efficient method for reconstructing sequences of MR images from undersampled k-space data.
abstract: In this paper, we propose a Compressive Sensing based approach to the problem of real-time reconstruction of MR image sequences. Our proposed method is able to extract useful priori information and incorporate it into a modified iterative thresholding algorithm for fast casual reconstruction of MR images from highly undersampled k-space data. Through extensive experimental results we show that our proposed method achieves superior reconstruction quality, while having a lower computational complexity and memory requirements compared to the other state-of-the-art methods.
authors.affiliation: Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore. Electronic address: dornoosh@nus.edu.sg.
authors.forename: Dornoosh
authors.initials: D
authors.lastname: Zonoobi
authors.affiliation: Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore. Electronic address: ashraf@nus.edu.sg.
authors.forename: Ashraf A
authors.initials: AA
authors.lastname: Kassim
mesh_terms: D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D015233:Models, Statistical; D058067:Wavelet Analysis
keywords: Dynamic MRI reconstruction; Iterative thresholding method; Priori-knowledge