A comparison of RIGR and SVD dynamic imaging methods

Jill M. Hanson, Zhi-Pei Liang, Richard L. Magin, Jeff L. Duerk, Paul C. Lauterbur

Research output: Contribution to journalArticlepeer-review


Several constrained imaging methods have recently been proposed for dynamic imaging applications. This paper compares two of these methods: the Reduced-encoding imaging by Generalized-series Reconstruction (RIGR) and Singular Value Decomposition (SVD) methods. RIGR utilizes a priori data for optimal image reconstruction whereas the SVD method seeks to optimize data acquisition. However, this study shows that the existing SVD encoding method tends to bias the data acquisition scheme toward reproducing the known features in the reference image. This characteristic of the SVD encoding method reduces its capability to capture new image features and makes it less suitable than RIGR for dynamic imaging applications.

Original languageEnglish (US)
Pages (from-to)161-167
Number of pages7
JournalMagnetic Resonance in Medicine
Issue number1
StatePublished - Jul 1997


  • Dynamic imaging
  • Fast imaging
  • Generalized series
  • Image reconstruction

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology


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