DLMRI-Lab: Dictionary Learning MRI Software. DLMRI is a formulation and an algorithm that adaptively learn a dictionary from undersampled k-space measurements and simultaneously reconstruct the MR image (this is an instance of so-called “blind compressed sensing”), as described in the following “DLMRI Paper”:  S. Ravishankar and Y. Bresler, “MR image reconstruction from highly undersampled k-space data by dictionary learning,” IEEE Trans. Med. Imag., vol. 30, no. 5, pp. 1028–1041, 2011.
Keywords for this software
References in zbMATH (referenced in 9 articles )
Showing results 1 to 9 of 9.
- Soltani, Sara; Andersen, Martin S.; Hansen, Per Christian: Tomographic image reconstruction using training images (2017)
- Ehrhardt, Matthias J.; Betcke, Marta M.: Multicontrast MRI reconstruction with structure-guided total variation (2016)
- Eksioglu, Ender M.: Decoupled algorithm for MRI reconstruction using nonlocal block matching model: BM3D-MRI (2016)
- Giryes, Raja: Sampling in the analysis transform domain (2016)
- Li, Yan-Ran; Chan, Raymond H.; Shen, Lixin; Hsu, Yung-Chin; Tseng, Wen-Yih Isaac: An adaptive directional Haar framelet-based reconstruction algorithm for parallel magnetic resonance imaging (2016)
- Bi, Dongjie; Xie, Yongle; Zheng, Yahong Rosa: Synthetic aperture radar imaging using basis selection compressed sensing (2015)
- Liu, Jianbo; Wang, Shanshan; Peng, Xi; Liang, Dong: Undersampled MR image reconstruction with data-driven tight frame (2015)
- Ravishankar, Saiprasad; Bresler, Yoram: Efficient blind compressed sensing using sparsifying transforms with convergence guarantees and application to magnetic resonance imaging (2015)
- Wang, Bigong; Li, Liang: Recent development of dual-dictionary learning approach in medical image analysis and reconstruction (2015)