Application of incremental algorithms to CT image reconstruction for sparse-view, noisy data

Sean Rose; Martin Skovgaard Andersen; Emil Y. Sidky; Xiaochuan Pan

Application of incremental algorithms to CT image reconstruction for sparse-view, noisy data

Sean Rose
, Martin Skovgaard Andersen
, Emil Y. Sidky
, Xiaochuan Pan

The University of Chicago

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

This conference contribution adapts an incremental framework for solving optimization problems of interest for sparse-view CT. From the incremental framework two algorithms are derived: one that combines a damped form of the algebraic reconstruction technique (ART) with a total-variation (TV) projection, and one that employs a modified damped ART, accounting for a weighted-quadratic data fidelity term, combined with TV projection. The algorithms are demonstrated on simulated, noisy, sparseview CT data.

Original language	English
Title of host publication	Proceedings of the 3rd International Conference on Image Formation in X-Ray Computed Tomography
Publication date	2014
Pages	351-354
Publication status	Published - 2014
Event	3rd International Conference on Image Formation in X-Ray Computed Tomography - Fort Douglas/Olympic Village, Salt Lake City, Utah, United States Duration: 22 Jun 2014 → 25 Jun 2014 Conference number: 3 http://www.ucair.med.utah.edu/CTmeeting/

Conference

Conference	3rd International Conference on Image Formation in X-Ray Computed Tomography
Number	3
Location	Fort Douglas/Olympic Village
Country/Territory	United States
City	Salt Lake City, Utah
Period	22/06/2014 → 25/06/2014
Internet address	http://www.ucair.med.utah.edu/CTmeeting/

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@inproceedings{5d6bd576b869426592d1b9a5c9c6c330,

title = "Application of incremental algorithms to CT image reconstruction for sparse-view, noisy data",

abstract = "This conference contribution adapts an incremental framework for solving optimization problems of interest for sparse-view CT. From the incremental framework two algorithms are derived: one that combines a damped form of the algebraic reconstruction technique (ART) with a total-variation (TV) projection, and one that employs a modified damped ART, accounting for a weighted-quadratic data fidelity term, combined with TV projection. The algorithms are demonstrated on simulated, noisy, sparseview CT data.",

author = "Sean Rose and Andersen, \{Martin Skovgaard\} and Sidky, \{Emil Y.\} and Xiaochuan Pan",

year = "2014",

language = "English",

pages = "351--354",

booktitle = "Proceedings of the 3rd International Conference on Image Formation in X-Ray Computed Tomography",

note = "3rd International Conference on Image Formation in X-Ray Computed Tomography ; Conference date: 22-06-2014 Through 25-06-2014",

url = "http://www.ucair.med.utah.edu/CTmeeting/",

}

Rose, S, Andersen, MS, Sidky, EY & Pan, X 2014, Application of incremental algorithms to CT image reconstruction for sparse-view, noisy data. in Proceedings of the 3rd International Conference on Image Formation in X-Ray Computed Tomography. pp. 351-354, 3rd International Conference on Image Formation in X-Ray Computed Tomography , Salt Lake City, Utah, United States, 22/06/2014. <http://www.ucair.med.utah.edu/CTmeeting/>

Application of incremental algorithms to CT image reconstruction for sparse-view, noisy data. / Rose, Sean; Andersen, Martin Skovgaard; Sidky, Emil Y. et al.
Proceedings of the 3rd International Conference on Image Formation in X-Ray Computed Tomography. 2014. p. 351-354.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Application of incremental algorithms to CT image reconstruction for sparse-view, noisy data

AU - Rose, Sean

AU - Andersen, Martin Skovgaard

AU - Sidky, Emil Y.

AU - Pan, Xiaochuan

N1 - Conference code: 3

PY - 2014

Y1 - 2014

N2 - This conference contribution adapts an incremental framework for solving optimization problems of interest for sparse-view CT. From the incremental framework two algorithms are derived: one that combines a damped form of the algebraic reconstruction technique (ART) with a total-variation (TV) projection, and one that employs a modified damped ART, accounting for a weighted-quadratic data fidelity term, combined with TV projection. The algorithms are demonstrated on simulated, noisy, sparseview CT data.

AB - This conference contribution adapts an incremental framework for solving optimization problems of interest for sparse-view CT. From the incremental framework two algorithms are derived: one that combines a damped form of the algebraic reconstruction technique (ART) with a total-variation (TV) projection, and one that employs a modified damped ART, accounting for a weighted-quadratic data fidelity term, combined with TV projection. The algorithms are demonstrated on simulated, noisy, sparseview CT data.

M3 - Article in proceedings

SP - 351

EP - 354

BT - Proceedings of the 3rd International Conference on Image Formation in X-Ray Computed Tomography

T2 - 3rd International Conference on Image Formation in X-Ray Computed Tomography

Y2 - 22 June 2014 through 25 June 2014

ER -

Application of incremental algorithms to CT image reconstruction for sparse-view, noisy data

Abstract

Conference

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