1. Cho J, Berman AJ, Gagoski B, et al. VUDU: motion-robust, distortion-free multi-shot EPI. In: Proceedings of the 29th Scientific Meeting of ISMRM. Online Conference; p.
2. Cho J, Kim TH, Gagoski B, et al. Variable Flip, Blip-Up and -Down Undersampling (VUDU) Enables Motion-Robust, Distortion-Free Multi-Shot EPI. In: Proceedings of the 30th Scientific Meeting of ISMRM. London, UK; p.
3. Liao C, Cao X, Cho J, Zhang Z, Setsompop K, Bilgic B. Highly efficient MRI through multi-shot echo planar imaging. In: Wavelets and Sparsity XVIII. Vol.
4. Liao C, Bilgic B, Tian Q, et al. Distortion-free, high-isotropic-resolution diffusion MRI with gSlider BUDA-EPI and multicoil dynamic B0 shimming. Magn. Reson. Med. 2021;86:791–803 doi: 10.1002/mrm.28748. [doi]
5. Polimeni JR, Bhat H, Witzel T, et al. Reducing sensitivity losses due to respiration and motion in accelerated echo planar imaging by reordering the autocalibration data acquisition: Reducing Losses in Accelerated EPI with FLEET-ACS. Magn. Reson. Med. 2016;75:665–679 doi: 10.1002/mrm.25628. [doi]
6. Berman AJ, Grissom WA, Witzel T, et al. Segmented spin-echo BOLD fMRI using a variable flip angle FLEET acquisition with recursive RF pulse design for high spatial resolution fMRI. In: Proceedings of 28th Annual Meeting of ISMRM. Paris, France. ; 2020. p.
7. Manhard MK, Stockmann J, Liao C, et al. A multi‐inversion multi‐echo spin and gradient echo echo planar imaging sequence with low image distortion for rapid quantitative parameter mapping and synthetic image contrasts. Magn. Reson. Med. 2021;86:866–880.
8. Zhang Z, Cho J, Wang L, et al. Blip up-down acquisition for spin- and gradient-echo imaging (BUDA-SAGE) with self-supervised denoising enables efficient T2, T2*, para- and dia-magnetic susceptibility mapping. Magn. Reson. Med. 2022;88:633–650 doi: 10.1002/mrm.29219. [doi]
9. Zhang Z, Ye H, Li M, Liu H, Bilgic B. Liver-Buda-Sage: Simultaneous Whole Liver T 2 and T* 2 Mapping in one Breath-Hold. In: 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). IEEE; 2022. pp. 1–5.
10. Haldar JP. Low-rank modeling of local k-space neighborhoods (LORAKS) for constrained MRI. IEEE Trans. Med. Imaging 2013;33:668–681.
11. Bilgic B, Kim TH, Liao C, et al. Improving parallel imaging by jointly reconstructing multi‐contrast data. Magn. Reson. Med. 2018;80:619–632.
12. Kim TH, Bilgic B, Polak D, Setsompop K, Haldar JP. Wave‐LORAKS: Combining wave encoding with structured low‐rank matrix modeling for more highly accelerated 3D imaging. Magn. Reson. Med. 2019;81:1620–1633.
13. Andersson JLR, Skare S, Ashburner J. How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging. NeuroImage 2003;20:870–888 doi: 10.1016/S1053-8119(03)00336-7. [doi]
14. Smith SM, Jenkinson M, Woolrich MW, et al. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 2004;23:S208–S219.
15. Zhang K, Zuo W, Chen Y, Meng D, Zhang L. Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising. IEEE Trans. Image Process. 2017;26:3142–3155.
16. Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE: sensitivity encoding for fast MRI. Magn. Reson. Med. Off. J. Int. Soc. Magn. Reson. Med. 1999;42:952–962.
17. Kim TH, Garg P, Haldar JP. LORAKI: Autocalibrated Recurrent Neural Networks for Autoregressive MRI Reconstruction in k-Space. ArXiv190409390 Cs Eess 2019.
19. Setsompop K, Fan Q, Stockmann J, et al. High-resolution in vivo diffusion imaging of the human brain with generalized slice dithered enhanced resolution: Simultaneous multislice (gSlider-SMS). Magn. Reson. Med. 2018;79:141–151 doi: 10.1002/mrm.26653. [doi]
20. International Society for Optics and Photonics; 2019. p.