Compressed Sensing MRI Using Sparsity Averaging and FISTA
- Autores: Huang J.1, Zhu L.1, Wang L.2, Song W.1
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Afiliações:
- College of Mechanical and Electrical Engineering, Northeast Forestry University
- College of Computer Science and Technology, Guizhou University
- Edição: Volume 48, Nº 8 (2017)
- Páginas: 749-760
- Seção: Original Paper
- URL: https://journals.rcsi.science/0937-9347/article/view/247825
- DOI: https://doi.org/10.1007/s00723-017-0910-0
- ID: 247825
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Resumo
Magnetic resonance imaging (MRI) is widely adopted for clinical diagnosis due to its non-invasively detection. However, acquisition of full k-space data limits its imaging speed. Compressed sensing (CS) provides a new technique to significantly reduce the measurements with high-quality MR image reconstruction. The sparsity of the MR images is one of the crucial bases of CS-MRI. In this paper, we present to use sparsity averaging prior for CS-MRI reconstruction in the basis of that MR images have average sparsity over multiple wavelet frames. The problem is solved using a Fast Iterative Shrinkage Thresholding Algorithm (FISTA), each iteration of which includes a shrinkage step. The performance of the proposed method is evaluated for several types of MR images. The experiment results illustrate that our approach exhibits a better performance than those methods that using redundant frame or a single orthonormal basis to promote sparsity.
Sobre autores
Jian-ping Huang
College of Mechanical and Electrical Engineering, Northeast Forestry University
Autor responsável pela correspondência
Email: jianping829@gmail.com
República Popular da China, Harbin, Heilongjiang Province, 150040
Liang-kuan Zhu
College of Mechanical and Electrical Engineering, Northeast Forestry University
Email: jianping829@gmail.com
República Popular da China, Harbin, Heilongjiang Province, 150040
Li-hui Wang
College of Computer Science and Technology, Guizhou University
Email: jianping829@gmail.com
República Popular da China, Huaxi District, Guiyang, 550025
Wen-long Song
College of Mechanical and Electrical Engineering, Northeast Forestry University
Email: jianping829@gmail.com
República Popular da China, Harbin, Heilongjiang Province, 150040