2022 Joint Annual Meeting ISMRM-ESMRMB and ISMRT 31st Annual Meeting
7 May 2022 – 15 May 2022 · London, United Kingdom
4348 ISMRM Abstract

Rapid reconstruction of Blip up-down circular EPI (BUDA-cEPI) for distortion-free dMRI using an Unrolled Network with U-Net as Priors

4348 · Machine Learning & Artificial Intelligence III · Wednesday, 11 May, 9:15 AM–11:15 AM · Gather.town Space: North East  Room: 2
Accepted
Uten Yarach 1, Itthi Chatnuntawech2, Congyu Liao3, Surat Teerapittayanon2, Siddharth Srinivasan Iyer3,4, Tae Hyung Kim5,6, Jaejin Cho5,6, Berkin Bilgic5,6, Yuxin Hu7, Brian A Hargreaves3,7,8, Kawin Setsompop3,7
1Department of Radiologic Technology, Faculty of Associated Medical Science, Chiang Mai University, Chiang Mai, Thailand
2National Nanotechnology Center (NANOTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand
3Department of Radiology, Stanford University, Stanford, United States of America
4Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, United States of America
5Athinoula A. Martinos Center for Biomedical Imaging, Cambridge, United States of America
6Department of Radiology, Harvard Medical School, Boston, United States of America
7Department of Electrical Engineering, Stanford University, Stanford, United States of America
8Department of Bioengineering, Stanford University, Stanford, United States of America
Presenting Author: Uten Yarach
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References

1. Bilgic B, Chatnuntawech I, Manhard MK, et al. Highly accelerated multishot echo planar imaging through synergistic machine learning and joint reconstruction. Magn Reson Med. 2019; 82:1343- 1358 2. Liao C, Bilgic B, Tian Q, Stockmann JP, Cao X, Fan Q, Iyer SS, Wang F, Ngamsombat C, Lo WC, Manhard MK, Huang SY, Wald LL, Setsompop K. Distortion-free, high-isotropic-resolution diffusion MRI with gSlider BUDA-EPI and multicoil dynamic B0 shimming. Magn Reson Med. 2021; 86(2): 791-803.
2. Cao X, Wang K, Liao C, Zhang Z, Srinivasan Iyer S, Chen Z, Lo WC, Liu H, He H, Setsompop K, Zhong J, Bilgic B. Efficient T2 mapping with blip-up/down EPI and gSlider-SMS (T2 -BUDA-gSlider). Magn Reson Med. 2021; 86(4): 2064-2075 4. Haldar JP. Low-rank modeling of local k-space neighborhoods (LORAKS) for constrained MRI. IEEE Trans Med Imaging. 2014; 33(3): 668-81.
3. Mani M, Jacob M, Kelley D, Magnotta V. Multi-shot sensitivity-encoded diffusion data recovery using structured low-rank matrix completion (MUSSELS). Magn Reson Med. 2017; 78(2): 494-507.
4. Aggarwal H, Mani M, and Jacob M. Multi-shot sensitivity-encoded diffusion MRI using model-based deep learning (MODL-MUSSELS). arXiv preprint arXiv:1812.08115, 2018. 7.Hu, Y, Xu, Y, Tian, Q, et al. RUN-UP: Accelerated multishot diffusion-weighted MRI reconstruction using an unrolled network with U-Net as priors. Magn Reson Med. 2020; 85: 709– 72.
5. Congyu ISMRM 2022 9. Rettenmeier C, Maziero D, Qian Y, Stenger VA. A circular echo planar sequence for fast volumetric fMRI. Magn Reson Med. 2019; 81(3):1685-1698.
6. O. Ronneberger, P. Fischer, and T. Brox, “U-net: Convolutional networks for biomedical image segmentation,” in International Conference on Medical image computing and computer-assisted intervention, (2015), pp. 234–241.
7. Abadi M., Barham P., Chen J. et al. TensorFlow: A System for Large-Scale Machine Learning. OSDI , 16, page 265-283. (2016).
8. Kingma D, Ba J, Adam: a method for stochastic optimization, Proc. Int. Conf. Learn. Represent. 2015 1–41.
9. Uecker M, Lai P, Murphy MJ, Virtue P, Elad M, Pauly JM, Vasanawala SS, Lustig M. ESPIRiT—an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA. Magn Reson Med 2014; 71: 990– 1001.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2022/4348