A Bayesian-MAP Method Based on TV for CT Image Reconstruction from Sparse and Limited Data

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    摘要 Computedtomography(CT)playsanimportantroleinthefieldofmodernmedicalimaging.Reducingradiationexposuredosewithoutsignificantlydecreasingimage'squalityisalwaysacrucialissue.Inspiredbytheoutstandingperformanceoftotalvariation(TV)techniqueinCTimagereconstruction,aTVregularizationbasedBayesian-MAP(MAP-TV)isproposedtoreconstructthecaseofsparseviewprojectionandlimitedanglerangeimaging.Thismethodcansuppressthestreakartifactsandgeometricaldeformationwhilepreservingimageedges.Weusedorderedsubset(OS)techniquetoacceleratethereconstructionspeed.NumericalresultsshowthatMAP-TVisabletoreconstructaphantomwithbettervisualperformanceandquantitativeevaluationthanclassicalFBP,MLEMandquadratepriortoMAPalgorithms.Theproposedalgorithmcanbegeneralizedtocone-beamCTimagereconstruction.
    机构地区 不详
    出版日期 2017年02月12日(中国Betway体育网页登陆平台首次上网日期,不代表论文的发表时间)
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