MR images from fewer data

Bahareh Vafadar; Philip J. Bones

doi:10.1117/12.930926

15 October 2012 MR images from fewer data

Bahareh Vafadar, Philip J. Bones

Proceedings Volume 8500, Image Reconstruction from Incomplete Data VII; 850003 (2012) https://doi.org/10.1117/12.930926
Event: SPIE Optical Engineering + Applications, 2012, San Diego, California, United States

Abstract

There is a strong motivation to reduce the amount of acquired data necessary to reconstruct clinically useful MR images, since less data means faster acquisition sequences, less time for the patient to remain motionless in the scanner and better time resolution for observing temporal changes within the body. We recently introduced an improvement in image quality for reconstructing parallel MR images by incorporating a data ordering step with compressed sensing (CS) in an algorithm named `PECS'. That method requires a prior estimate of the image to be available. We are extending the algorithm to explore ways of utilizing the data ordering step without requiring a prior estimate. The method presented here first reconstructs an initial image x₁ by compressed sensing (with scarcity enhanced by SVD), then derives a data ordering from x₁, R'₁ , which ranks the voxels of x₁ according to their value. A second reconstruction is then performed which incorporates minimization of the first norm of the estimate after ordering by R'₁ , resulting in a new reconstruction x₂. Preliminary results are encouraging.

Citation Download Citation

Bahareh Vafadar and Philip J. Bones "MR images from fewer data", Proc. SPIE 8500, Image Reconstruction from Incomplete Data VII, 850003 (15 October 2012); https://doi.org/10.1117/12.930926

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