Abstract
A novel class of k-space trajectories for magnetic resonance imaging (MRI) sampling using space filling curves (SFCs) is presented here. More specifically, Peano, Hilbert and Sierpinski curves are used. We propose 1-shot and 4-shot variable density SFCs by utilizing the space coverage provided by SFCs in different iterations. The proposed trajectories are compared with state-of-the-art echo planar imaging (EPI) trajectories for 128 × 128 and 256 × 256 phantom and brain images. The simulation results show that the readout time is reduced by up to 45% for the 128 × 128 image with little compromise in reconstruction quality. Also, the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) index are improved by 2.32 dB and 0.1009, respectively, with an 18% shorter readout time using the 4-shot Hilbert SFC trajectory for reconstructing a 256 × 256 brain MRI image.
| Original language | English |
|---|---|
| Title of host publication | ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
| Subtitle of host publication | Proceedings |
| Publisher | IEEE |
| Pages | 1115-1119 |
| Number of pages | 5 |
| ISBN (Electronic) | 978-1-5090-6631-5 |
| ISBN (Print) | 978-1-5090-6632-2 |
| DOIs | |
| Publication status | Published - 2020 |
| Event | ICASSP 2020: IEEE International Conference on Acoustics, Speech and Signal Processing - Barcelona, Spain Duration: 4 May 2020 → 8 May 2020 |
Conference
| Conference | ICASSP 2020 |
|---|---|
| Country/Territory | Spain |
| City | Barcelona |
| Period | 4/05/20 → 8/05/20 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Keywords
- MRI
- k-space trajectories
- space filling curves