Accelerating magnetic resonance imaging via deep learning

Proceedings - International Symposium on Biomedical Imaging

Volumn 2016-June, Issue , 2016, Pages 514-517

  Wang, Shanshan ^a   Su, Zhenghang ^b   Ying, Leslie ^c   Peng, Xi ^a   Zhu, Shun ^a   Liang, Feng ^d   Feng, Dagan ^e   Liang, Dong ^a  

^a SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY   (China)

^b GUANGDONG UNIVERSITY OF TECHNOLOGY   (China)

^c UNIVERSITY AT BUFFALO   (United States)

^d NANKAI UNIVERSITY   (China)

^e UNIVERSITY OF SYDNEY   (Australia)

Author keywords

convolutional neural network; Deep learning; magnetic resonance imaging; prior knowledge

Indexed keywords

CONVOLUTION; MAGNETIC LEVITATION VEHICLES; MAGNETISM; MEDICAL IMAGING; NEURAL NETWORKS; RESONANCE;

CONSTRAINED RECONSTRUCTION; CONVOLUTIONAL NEURAL NETWORK; DEEP LEARNING; FINE STRUCTURES; K-SPACE DATUM; MAPPING RELATIONSHIPS; PRIOR KNOWLEDGE; TRAINING DATA SETS;

MAGNETIC RESONANCE IMAGING;

EID: 84978427520     PISSN: 19457928     EISSN: 19458452     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2016.7493320     Document Type: Conference Paper

References (9)

1. M. Lustig and J. M. Pauly, "SPIRiT: Iterative self-consistent parallel imaging reconstruction from arbitrary k-space, " Magn. Reson. Med., vol. 64, no. 2, pp. 457-471, 2010.
2. F. Knoll, C. Clason, K. Bredies, M. Uecker, and R. Stollberger, "Parallel imaging with nonlinear reconstruction using variational penalties, " Magn. Reson. Med., vol. 67, no. 1, pp. 34-41, 2012.
3. Zhi-Pei Liang, "Spatiotemporal imaging with partially separable functions, " in Proceedings International Symposium on Biomedical Imaging (ISBI). IEEE, 2007, pp. 181-182.
4. Justin P Haldar and Zhi-Pei Liang, "Spatiotemporal imaging with partially separable functions: A matrix recovery approach, " in Proceedings International Symposium on Biomedical Imaging (ISBI). IEEE, 2010, pp. 716-719.
5. Zhi-Pei Liang, Bruno Madore, Gary H Glover, and Norbert J Pelc, "Fast algorithms for gs-model-based image reconstruction in data-sharing fourier imaging, " IEEE Trans. Med. Imaging, vol. 22, no. 8, pp. 1026-1030, 2003.
6. Yunmei Chen, William W. Hager, Feng Huang, Dzung T. Phan, Xiaojing Ye, and Wotao Yin, "Fast algorithms for image reconstruction with application to partially parallel MR imaging, " SIAM J. Imaging Sciences, vol. 5, no. 1, pp. 90-118, 2012.
7. Shanshan Wang, Yong Xia, Qiegen Liu, Pei Dong, David Dagan Feng, and Jianhua Luo, "Fenchel duality based dictionary learning for restoration of noisy images, " IEEE Transactions on Image Processing, vol. 22, no. 12, pp. 5214-5225, 2013.
8. Wanli Ouyang, Xiaogang Wang, Xingyu Zeng, Shi Qiu, Ping Luo, Yonglong Tian, Hongsheng Li, Shuo Yang, Zhe Wang, Chen-Change Loy, et al., "Deepid-net: Deformable deep convolutional neural networks for object detection, " in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 2403-2412.
9. Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang, "Learning a deep convolutional network for image superresolution, " in Computer Vision-ECCV 2014, pp. 184-199. Springer, 2014.