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Image reconstruction by an alternating minimisation
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Indexed by:期刊论文

Date of Publication:2011-02-01

Journal:NEUROCOMPUTING

Included Journals:Scopus、SCIE、EI

Volume:74

Issue:5

Page Number:661-670

ISSN No.:0925-2312

Key Words:Limited angle tomography; III-posed inverse problem; Total variation (TV)

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. (C) 2010 Elsevier B.V. All rights reserved.

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Gender:Female

Alma Mater:大连理工大学

Degree:Doctoral Degree

School/Department:信息与通信工程学院

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