2020 ISMRM and SMRT Virtual Conference and Exhibition
8 August 2020 – 14 August 2020 · Online, Virtual
0969 ISMRM Abstract

DeepDTI: Six-direction diffusion tensor MRI using deep learning

Accepted
Qiyuan Tian 1,2, Berkin Bilgic1,2, Qiuyun Fan1,2, Congyu Liao1,2, Chanon Ngamsombat1, Yuxin Hu3, Thomas Witzel1, Kawin Setsompop1,2, Jonathan R Polimeni1,2, Susie Huang1,2
1Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, United States of America
2Department of Radiology, Harvard Medical School, Boston, United States of America
3Department of Electrical Engineering, Stanford University, Stanford, United States of America
Presenting Author: Qiyuan Tian
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References

1. [7] Golkov, V. et al. q-Space deep learning: twelve-fold shorter and model-free diffusion MRI scans. IEEE transactions on medical imaging 35, 1344-1351 (2016). [8] Skare, S., Hedehus, M., Moseley, M. E. & Li, T.-Q. Condition number as a measure of noise performance of diffusion tensor data acquisition schemes with MRI. Journal of Magnetic Resonance 147, 340-352 (2000). [9] Zhang, K., Zuo, W., Chen, Y., Meng, D. & Zhang, L. Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising. IEEE Transactions on Image Processing 26, 3142-3155 (2017). [10] Kim, J., Kwon Lee, J. & Mu Lee, K. Accurate image super-resolution using very deep convolutional networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1646-1654 (2016). [11] Simonyan, K. & Zisserman, A. Very deep convolutional networks for large-scale image recognition. Preprint at: https://arxiv.org/abs/1409.1556 (2014). [12] Glasser, M. F. et al. The minimal preprocessing pipelines for the Human Connectome Project. NeuroImage 80, 105-124 (2013). [13] Maggioni, M., Katkovnik, V., Egiazarian, K. & Foi, A. Nonlocal transform-domain filter for volumetric data denoising and reconstruction. IEEE transactions on image processing 22, 119-133 (2012). [14] Dabov, K., Foi, A., Katkovnik, V. & Egiazarian, K. Image denoising by sparse 3-D transform-domain collaborative filtering. IEEE Transactions on image processing 16, 2080-2095 (2007). [15] Veraart, J., Fieremans, E. & Novikov, D. S. Diffusion MRI noise mapping using random matrix theory. Magnetic resonance in medicine 76, 1582-1593 (2016). [16] Veraart, J. et al. Denoising of diffusion MRI using random matrix theory. NeuroImage 142, 394-406 (2016).

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