Literature DB >> 24105815

Application of the compressed sensing technique to self-gated cardiac cine sequences in small animals.

Paula Montesinos1, Juan Felipe P J Abascal, Lorena Cussó, Juan José Vaquero, Manuel Desco.   

Abstract

PURPOSE: Self-gated cine sequences are a common choice for cardiac MRI in preclinical applications. The aims of our work were to apply the compressed sensing technique to IntraGateFLASH cardiac MRI studies on rats and to find the maximum acceleration factor achievable with this technique. THEORY AND METHODS: Our reconstruction method extended the Split Bregman formulation to minimize the total variation in both space and time. In addition, we analyzed the influence of the undersampling pattern on the acceleration factor achievable.
RESULTS: Our results show that acceleration factors of up to 15 are achievable with our technique when appropriate undersampling patterns are used. The introduction of a time-varying random sampling clearly improved the efficiency of the undersampling schemes. In terms of computational efficiency, the proposed reconstruction method has been shown to be competitive as compared with the fastest methods found in the literature.
CONCLUSION: We successfully applied our compressed sensing technique to self-gated cardiac cine acquisition in small animals, obtaining an acceleration factor of up to 15 with almost unnoticeable image degradation.
Copyright © 2013 Wiley Periodicals, Inc.

Entities:  

Keywords:  Split Bregman; cardiac cine MRI; compressed sensing; self-gated; total variation; undersampling pattern

Mesh:

Year:  2013        PMID: 24105815     DOI: 10.1002/mrm.24936

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  9 in total

1.  Investigation of different sparsity transforms for the PICCS algorithm in small-animal respiratory gated CT.

Authors:  Juan F P J Abascal; Monica Abella; Alejandro Sisniega; Juan Jose Vaquero; Manuel Desco
Journal:  PLoS One       Date:  2015-04-02       Impact factor: 3.240

2.  Comparison of total variation with a motion estimation based compressed sensing approach for self-gated cardiac cine MRI in small animal studies.

Authors:  Juan F P J Abascal; Paula Montesinos; Eugenio Marinetto; Javier Pascau; Manuel Desco
Journal:  PLoS One       Date:  2014-10-28       Impact factor: 3.240

3.  Magnetic Induction Tomography Spectroscopy for Structural and Functional Characterization in Metallic Materials.

Authors:  Imamul Muttakin; Manuchehr Soleimani
Journal:  Materials (Basel)       Date:  2020-06-09       Impact factor: 3.623

4.  Electrical Resistance Tomography for Visualization of Moving Objects Using a Spatiotemporal Total Variation Regularization Algorithm.

Authors:  Bo Chen; Juan F P J Abascal; Manuchehr Soleimani
Journal:  Sensors (Basel)       Date:  2018-05-24       Impact factor: 3.576

5.  Accelerated free-breathing 3D T1ρ cardiovascular magnetic resonance using multicoil compressed sensing.

Authors:  Srikant Kamesh Iyer; Brianna Moon; Eileen Hwuang; Yuchi Han; Michael Solomon; Harold Litt; Walter R Witschey
Journal:  J Cardiovasc Magn Reson       Date:  2019-01-10       Impact factor: 5.364

6.  Artificial skin through super-sensing method and electrical impedance data from conductive fabric with aid of deep learning.

Authors:  Xi Duan; Sebastien Taurand; Manuchehr Soleimani
Journal:  Sci Rep       Date:  2019-06-20       Impact factor: 4.379

7.  Development of Real-Time Magnetic Resonance Imaging of Mouse Hearts at 9.4 Tesla--Simulations and First Application.

Authors:  Tobias Wech; Nicole Seiberlich; Andreas Schindele; Vicente Grau; Leonie Diffley; Michael L Gyngell; Alfio Borzì; Herbert Köstler; Jurgen E Schneider
Journal:  IEEE Trans Med Imaging       Date:  2015-11-19       Impact factor: 10.048

8.  MR fingerprinting with simultaneous B1 estimation.

Authors:  Guido Buonincontri; Stephen J Sawiak
Journal:  Magn Reson Med       Date:  2015-10-28       Impact factor: 4.668

9.  Three-dimensional self-gated cardiac MR imaging for the evaluation of myocardial infarction in mouse model on a 3T clinical MR system.

Authors:  Xiaoyong Zhang; Bensheng Qiu; Zijun Wei; Fei Yan; Caiyun Shi; Shi Su; Xin Liu; Jim X Ji; Guoxi Xie
Journal:  PLoS One       Date:  2017-12-07       Impact factor: 3.240

  9 in total

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