Image reconstruction by an alternating minimisation

Xiaoqiang Lu, Yi Sun, Yuan Yuan

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

This paper focuses on the problem of incomplete data in the applications of the circular cone-beam computed tomography. This problem is frequently encountered in medical imaging sciences and some other industrial imaging systems. For example, it is crucial when the high density region of objects can only be penetrated by X-rays in a limited angular range. As the projection data are only available in an angular range, the above mentioned incomplete data problem can be attributed to the limited angle problem, which is an ill-posed inverse problem. This paper reports a modified total variation minimisation method to reduce the data insufficiency in tomographic imaging. This proposed method is robust and efficient in the task of reconstruction by showing the convergence of the alternating minimisation method. The results demonstrate that this new reconstruction method brings reasonable performance.

Original languageEnglish
Pages (from-to)661-670
Number of pages10
JournalNeurocomputing
Volume74
Issue number5
DOIs
StatePublished - Feb 2011
Externally publishedYes

Keywords

  • Ill-posed inverse problem
  • Limited angle tomography
  • Total variation (TV)

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