title: An iterative reduced field-of-view reconstruction for periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) MRI.
abstract: OBJECTIVE
  To propose a new reduced field-of-view (rFOV) strategy for iterative reconstructions in a clinical environment. Iterative reconstructions can incorporate regularization terms to improve the image quality of periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) MRI. However, the large amount of calculations required for full FOV iterative reconstructions has posed a huge computational challenge for clinical usage. By subdividing the entire problem into smaller rFOVs, the iterative reconstruction can be accelerated on a desktop with a single graphic processing unit (GPU).
  
  
  METHODS
  This rFOV strategy divides the iterative reconstruction into blocks, based on the block-diagonal dominant structure. A near real-time reconstruction system was developed for the clinical MR unit, and parallel computing was implemented using the object-oriented model. In addition, the Toeplitz method was implemented on the GPU to reduce the time required for full interpolation. Using the data acquired from the PROPELLER MRI, the reconstructed images were then saved in the digital imaging and communications in medicine format.
  
  
  RESULTS
  The proposed rFOV reconstruction reduced the gridding time by 97%, as the total iteration time was 3 s even with multiple processes running. A phantom study showed that the structure similarity index for rFOV reconstruction was statistically superior to conventional density compensation (p < 0.001). In vivo study validated the increased signal-to-noise ratio, which is over four times higher than with density compensation. Image sharpness index was improved using the regularized reconstruction implemented.
  
  
  CONCLUSIONS
  The rFOV strategy permits near real-time iterative reconstruction to improve the image quality of PROPELLER images. Substantial improvements in image quality metrics were validated in the experiments. The concept of rFOV reconstruction may potentially be applied to other kinds of iterative reconstructions for shortened reconstruction duration.
authors.affiliation: Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, United Kingdom.
authors.forename: Jyh-Miin
authors.initials: JM
authors.lastname: Lin
authors.affiliation: Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, United Kingdom.
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Patterson
authors.affiliation: Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, LG3, The Hong Kong Jockey Club for Interdisciplinary Research, 5 Sassoon Road, Pokfulam, Hong Kong.
authors.forename: Hing-Chiu
authors.initials: HC
authors.lastname: Chang
authors.affiliation: Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, United Kingdom.
authors.forename: Jonathan H
authors.initials: JH
authors.lastname: Gillard
authors.affiliation: Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, United Kingdom.
authors.forename: Martin J
authors.initials: MJ
authors.lastname: Graves
mesh_terms: D003196:Computer Graphics; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D019047:Phantoms, Imaging; D012399:Rotation