relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1358/ title: Chaotic Compressed Sensing and its Application in Magnetic Resonance Imaging creator: Nguyen, Linh Trung creator: Truong, Minh Chinh creator: Tran, Duc Tan creator: Le, Vu Ha creator: Do, Ngoc Minh subject: Communications subject: Electronics and Communications subject: Electronics and Computer Engineering description: Fast image acquisition in magnetic resonance imaging (MRI) is important, due to the need to find ways that help relieve patient’s stress during MRI scans. Methods for fast MRI have been proposed, most notably among them are pMRI (parallel MRI), SWIFT (SWeep Imaging with Fourier Transformation), and compressed sensing (CS) based MRI. Although it promises to significantly reduce acquisition time, applying CS to MRI leads to difficulties with hardware design because of the randomness nature of the measurement matrix used by the conventional CS methods. In this paper, we propose a novel method that combines the above-mentioned three approaches for fast MRI by designing a compound measurement matrix from a series of single measurement matrices corresponding to pMRI, SWIFT, and CS. In our method, the CS measurement matrix is designed to be deterministic via chaotic systems. This chaotic compressed sensing (CCS) measurement matrix, while retaining most features of the random CS matrix, is simpler to realize in hardware. Several compound measurement matrices have been constructed and examined in this work, including CCS-MRI, CCS-pMRI, CCS-SWIFT, and CCS-pSWIFT. Simulation results showed that the proposed method allows an increase in the speed of the MRI acquisition process while not compromising the quality of the acquired MR images. publisher: REV date: 2013-12-01 type: Article type: PeerReviewed format: application/pdf language: en identifier: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1358/1/jec_2013-0201.pdf identifier: Nguyen, Linh Trung and Truong, Minh Chinh and Tran, Duc Tan and Le, Vu Ha and Do, Ngoc Minh (2013) Chaotic Compressed Sensing and its Application in Magnetic Resonance Imaging. REV Journal on Electronics and Communications, 3 (3-4). pp. 84-92. ISSN 1859-387X relation: 10.21553/rev-jec.60