id: 05937906
dt: j
an: 05937906
au: Lu, Xiaoqiang; Sun, Yi; Yuan, Yuan
ti: Optimization for limited angle tomography in medical image processing.
so: Pattern Recognition 44, No. 10-11, 2427-2435 (2011).
py: 2011
pu: Elsevier Science Ltd. (Pergamon), Oxford
la: EN
cc: 
ut: ill-posed inverse problem; total variation (TV)
ci: 
li: doi:10.1016/j.patcog.2010.12.016
ab: Summary: This paper aims to reduce the problems of incomplete data in
    computed tomography, which happens frequently in medical image
    processing and analysis, e.g., when the high-density region of objects
    can only be penetrated by X-rays at a limited angular range. As the
    projection data are available only in an angular range, the incomplete
    data problem can be attributed to the limited angle problem, which is
    an ill-posed inverse problem. Image reconstruction based on total
    variation (TV) reduces the problem and gives better performance on
    edge-preserving reconstruction; however, the artificial parameter can
    only be determined through considerable experimentation. In this paper,
    an effective TV objective function is proposed to reduce the inverse
    problem in the limited angle tomography. This novel objective function
    provides a robust and effective reconstruction without any artificial
    parameter in the iterative processes, using the TV as a multiplicative
    constraint. The results demonstrate that this reconstruction strategy
    outperforms some previous ones.
rv: