VNU-UET Repository

Chaotic Compressed Sensing and its Application in Magnetic Resonance Imaging

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

[img] PDF
Download (743kB)


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.

Item Type: Article
Subjects: Electronics and Communications > Communications
Electronics and Communications
Electronics and Communications > Electronics and Computer Engineering
Divisions: Faculty of Electronics and Telecommunications (FET)
Depositing User: Lê Vũ Hà
Date Deposited: 06 Sep 2015 08:10
Last Modified: 30 Aug 2016 08:23

Actions (login required)

View Item View Item