2013/02/01 by Zai Yang, Yang, Zai, Cishen Zhang +3 · 1 citation
Engineering · Medicine · #Advanced MRI Techniques and Applications #Biological Physics (physics.bio-ph) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Physical sciences #Medical Physics (physics.med-ph) #Photoacoustic and Ultrasonic Imaging #Sparse and Compressive Sensing Techniques
paper · pdf · doi:10.48550/arxiv.1302.0077
openalex publication_date 2013/02/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
MR image sparsity/compressibility has been widely exploited for imaging acceleration with the development of compressed sensing. A sparsity-based approach to rigid-body motion correction is presented for the first time in this paper. A motion is sought after such that the compensated MR image is maximally sparse/compressible among the infinite candidates. Iterative algorithms are proposed that jointly estimate the motion and the image content. The proposed method has a lot of merits, such as no need of additional data and loose requirement for the sampling sequence. Promising results are presented to demonstrate its performance.