@inproceedings{743092dd152e4508a651ff225922ecfc,
title = "Parallel imaging via sparse representation over a learned dictionary",
abstract = "This paper proposes an adaptive reconstruction method for parallel imaging (PI) via sparse representation over a learned dictionary and also a corresponding dictionary learning based PI (DL-PI) algorithm. DL-PI adopts the 'divide and conquer' strategy to solve the ℓ2-DL reconstruction formulation, with dictionary learning to capture the structure information and a Taylor approximation to update the target image analytically. The proposed approach has been applied to parallel magnetic resonance imaging (MRI) and compared to two latest state-of-the-art methods. The experimental results on in-vivo data show that the DL-PI algorithm possesses strong ability in detail preservation and is competent in artifact removal during the MR image reconstruction process.",
keywords = "compressed sensing, dictionary learning, magnetic resonance imaging, Parallel imaging",
author = "Shanshan Wang and Xi Peng and Pei Dong and Leslie Ying and \{Dagan Feng\}, David and Dong Liang",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 ; Conference date: 16-04-2015 Through 19-04-2015",
year = "2015",
month = jul,
day = "21",
doi = "10.1109/ISBI.2015.7163966",
language = "English",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE Computer Society",
pages = "687--690",
booktitle = "2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015",
address = "United States",
}