Abstract

Background It was noted early-on that non-Cartesian parallel imaging is achievable by solving the k-space data consistency equation, with inclusion of coil sensitivity profiles [1]. This iterative method which uses gridding is successful [2,3], as is radial GRAPPA [4]. Here we present the first results of algebraic reconstruction technique (ART) [5,6] which also enforces data consistency. The use of ART with coil-map constraints for radial MRI reconstruction has only recently been described [5] and has not been explored for clinical applications.

Highlights

  • It was noted early-on that non-Cartesian parallel imaging is achievable by solving the k-space data consistency equation, with inclusion of coil sensitivity profiles [1]

  • Short axis cardiac cine data were acquired on a 1.5T Siemens Sonata (Erlangen, Germany), using segmented breath-held 2D radial balanced SSFP with 192 readout points

  • In the iterative algebraic reconstruction technique (ART) method [5] each k-space data point is processed, so that the difference between the predicted value, based on the encoding matrix and the current image estimate, and the actual k-space data point value is inverse encoded and this residual is added to the current image estimate, weighted by l

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Summary

Introduction

It was noted early-on that non-Cartesian parallel imaging is achievable by solving the k-space data consistency equation, with inclusion of coil sensitivity profiles [1]. Methods Short axis cardiac cine data were acquired on a 1.5T Siemens Sonata (Erlangen, Germany), using segmented breath-held 2D radial balanced SSFP with 192 readout points. TR/TE/θ= 2.9/1.5/60°, 36 cm FOV, 930 Hz/pixel, and 4-5 coils.

Results
Conclusion

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