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Author (up) Rodriguez-Alvarez, M.J.; Sanchez, F.; Soriano, A.; Iborra, A. doi  openurl
  Title Sparse Givens resolution of large system of linear equations: Applications to image reconstruction Type Journal Article
  Year 2010 Publication Mathematical and Computer Modelling Abbreviated Journal Math. Comput. Model.  
  Volume 52 Issue 7-8 Pages 1258-1264  
  Keywords Givens rotations; QR-factorization; Computed tomography; Image reconstruction  
  Abstract In medicine, computed tomographic images are reconstructed from a large number of measurements of X-ray transmission through the patient (projection data). The mathematical model used to describe a computed tomography device is a large system of linear equations of the form AX = B. In this paper we propose the QR decomposition as a direct method to solve the linear system. QR decomposition can be a large computational procedure. However, once it has been calculated for a specific system, matrices Q and R are stored and used for any acquired projection on that system. Implementation of the QR decomposition in order to take more advantage of the sparsity of the system matrix is discussed.  
  Address [Rodriguez-Alvarez, Maria-Jose; Iborra, Amadeo] Univ Politecn Valencia, Inst Matemat Multidisciplinar, E-46022 Valencia, Spain, Email: mjrodri@imm.upv.es  
  Corporate Author Thesis  
  Publisher Pergamon-Elsevier Science Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0895-7177 ISBN Medium  
  Area Expedition Conference  
  Notes ISI:000280933700043 Approved no  
  Is ISI yes International Collaboration no  
  Call Number IFIC @ elepoucu @ Serial 395  
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