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Publication Detail
Performance improvement and validation of a new MAP reconstruction algorithm
  • Publication Type:
    Conference
  • Authors:
    Tsai YJ, Bousse A, Stearns CW, Ahn S, Hutton BF, Arridge S, Thielemans K
  • Publisher:
    IEEE
  • Publication date:
    19/10/2017
  • Published proceedings:
    2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop, NSS/MIC/RTSD 2016
  • Volume:
    2017-January
  • ISBN-13:
    9781509016426
  • Status:
    Published
  • Name of conference:
    2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop, NSS/MIC/RTSD 2016
  • Conference place:
    Strasbourg, France
  • Conference start date:
    29/10/2016
  • Conference finish date:
    06/11/2016
Abstract
© 2016 IEEE. We previously proposed a fast maximum a posteriori (MAP) algorithm, limited-memory Broyden-Fletcher-Goldfarb- Shanno with boundary constrains (LBFGS-B-PC), combining LBFGS-B with diagonal preconditioning. Previous results have shown in simulations that it converges using around 40 projections independent of many factors. The aim of this study is to improve the algorithm further by using a better initial image and a modified preconditioner that is less sensitive to noise and data scale. By initializing the algorithm with the best initial image (one full iteration of OSEM with 35 subsets), ROI values can converge almost twice as fast for the same computation time. Moreover, the new preconditioner makes the performance more consistent between high and low count data sets. In addition, we have found a means to choose the stopping criteria to reach a desired level of quantitative accuracy in the reconstructed image. Based on the results with patient data, the optimized LBFGS-B-PC shows promise for clinical imaging.
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