Sparse Sampling and Fully-3D Fast Total Variation Based Imaging Reconstruction for Chemical Shift Imaging in Magnetic Resonance Spectroscopy

  • Zigen Song
  • Melinda Baxter
  • Mingwu Jin
  • Jian-Xiong Wang
  • Ren-Cang Li
  • Talon Johnson
  • Jianzhong SuEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11309)


We propose a 3-dimensional sparse sampling reconstruction method, aiming for chemical shift imaging in magnetic resonance spectroscopy. The method is a Compressed Sensing (CS) method based on the interior point optimization technique that can substantially reduce the number of sampling points required, and the method has been tested successfully in hyperpolarized 13C experimental data using two different sampling strategies.


Imaging reconstruction Chemical shift imaging 3D Compressed Sensing Sparse sampling of MRSI data 



Zigen Song’s research is supported in part by the National Natural Science Foundation of China under Grant No. 11672177.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Zigen Song
    • 1
    • 2
  • Melinda Baxter
    • 1
  • Mingwu Jin
    • 3
  • Jian-Xiong Wang
    • 4
  • Ren-Cang Li
    • 1
  • Talon Johnson
    • 1
  • Jianzhong Su
    • 1
    Email author
  1. 1.Department of MathematicsUniversity of Texas at ArlingtonArlingtonUSA
  2. 2.College of Information TechnologyShanghai Ocean UniversityShanghaiChina
  3. 3.Department of PhysicsUniversity of Texas at ArlingtonArlingtonUSA
  4. 4.Advanced Imaging Research Center Radiology DepartmentUniversity of Texas Southwestern Medical CenterDallasUSA

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