Accelerating regularized iterative ct reconstruction on commodity graphics hardware (GPU)

Wei Xu; Klaus Mueller

doi:10.1109/ISBI.2009.5193298

Accelerating regularized iterative ct reconstruction on commodity graphics hardware (GPU)

Wei Xu
, Klaus Mueller

Computer Science

Stony Brook University

Stony Brook University

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

4 Scopus citations

Abstract

Iterative reconstruction algorithms augmented with regularization can produce high-quality reconstructions from few views and even in the presence of significant noise. In this paper we focus on the particularities associated with the GPU acceleration of these. First, we introduce the idea of using exhaustive benchmark tests to determine the optimal settings of various parameters in iterative algorithm, here OS-SIRT, which proofs decisive for obtaining optimal GPU performance. Then we introduce bilateral filtering as a viable and cost-effective means for regularization, and we show that GPU-acceleration reduces its overhead to very moderate levels.

Original language	English
Title of host publication	Proceedings - 2009 IEEE International Symposium on Biomedical Imaging
Subtitle of host publication	From Nano to Macro, ISBI 2009
Publisher	IEEE Computer Society
Pages	1287-1290
Number of pages	4
ISBN (Print)	9781424439324
DOIs	https://doi.org/10.1109/ISBI.2009.5193298
State	Published - 2009
Event	6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 - Boston, MA, United States Duration: Jun 28 2009 → Jul 1 2009

Publication series

Name	Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009

Conference

Conference	6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009
Country/Territory	United States
City	Boston, MA
Period	06/28/09 → 07/1/09

Keywords

Bilateral filter
Computed tomography
GPU
Iterative reconstruction
Ordered subsets

Access to Document

10.1109/ISBI.2009.5193298

Cite this

Xu, W., & Mueller, K. (2009). Accelerating regularized iterative ct reconstruction on commodity graphics hardware (GPU). In Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 (pp. 1287-1290). Article 5193298 (Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009). IEEE Computer Society. https://doi.org/10.1109/ISBI.2009.5193298

@inproceedings{4190910d725f4d958ad7c42f5a187948,

title = "Accelerating regularized iterative ct reconstruction on commodity graphics hardware (GPU)",

abstract = "Iterative reconstruction algorithms augmented with regularization can produce high-quality reconstructions from few views and even in the presence of significant noise. In this paper we focus on the particularities associated with the GPU acceleration of these. First, we introduce the idea of using exhaustive benchmark tests to determine the optimal settings of various parameters in iterative algorithm, here OS-SIRT, which proofs decisive for obtaining optimal GPU performance. Then we introduce bilateral filtering as a viable and cost-effective means for regularization, and we show that GPU-acceleration reduces its overhead to very moderate levels.",

keywords = "Bilateral filter, Computed tomography, GPU, Iterative reconstruction, Ordered subsets",

author = "Wei Xu and Klaus Mueller",

year = "2009",

doi = "10.1109/ISBI.2009.5193298",

language = "English",

isbn = "9781424439324",

series = "Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009",

publisher = "IEEE Computer Society",

pages = "1287--1290",

booktitle = "Proceedings - 2009 IEEE International Symposium on Biomedical Imaging",

note = "6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 ; Conference date: 28-06-2009 Through 01-07-2009",

}

Xu, W & Mueller, K 2009, Accelerating regularized iterative ct reconstruction on commodity graphics hardware (GPU). in Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009., 5193298, Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009, IEEE Computer Society, pp. 1287-1290, 6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009, Boston, MA, United States, 06/28/09. https://doi.org/10.1109/ISBI.2009.5193298

Accelerating regularized iterative ct reconstruction on commodity graphics hardware (GPU). / Xu, Wei; Mueller, Klaus.
Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009. IEEE Computer Society, 2009. p. 1287-1290 5193298 (Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009).

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

TY - GEN

T1 - Accelerating regularized iterative ct reconstruction on commodity graphics hardware (GPU)

AU - Xu, Wei

AU - Mueller, Klaus

PY - 2009

Y1 - 2009

N2 - Iterative reconstruction algorithms augmented with regularization can produce high-quality reconstructions from few views and even in the presence of significant noise. In this paper we focus on the particularities associated with the GPU acceleration of these. First, we introduce the idea of using exhaustive benchmark tests to determine the optimal settings of various parameters in iterative algorithm, here OS-SIRT, which proofs decisive for obtaining optimal GPU performance. Then we introduce bilateral filtering as a viable and cost-effective means for regularization, and we show that GPU-acceleration reduces its overhead to very moderate levels.

AB - Iterative reconstruction algorithms augmented with regularization can produce high-quality reconstructions from few views and even in the presence of significant noise. In this paper we focus on the particularities associated with the GPU acceleration of these. First, we introduce the idea of using exhaustive benchmark tests to determine the optimal settings of various parameters in iterative algorithm, here OS-SIRT, which proofs decisive for obtaining optimal GPU performance. Then we introduce bilateral filtering as a viable and cost-effective means for regularization, and we show that GPU-acceleration reduces its overhead to very moderate levels.

KW - Bilateral filter

KW - Computed tomography

KW - GPU

KW - Iterative reconstruction

KW - Ordered subsets

UR - https://www.scopus.com/pages/publications/70449441017

U2 - 10.1109/ISBI.2009.5193298

DO - 10.1109/ISBI.2009.5193298

M3 - Conference contribution

SN - 9781424439324

T3 - Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009

SP - 1287

EP - 1290

BT - Proceedings - 2009 IEEE International Symposium on Biomedical Imaging

PB - IEEE Computer Society

T2 - 6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009

Y2 - 28 June 2009 through 1 July 2009

ER -

Xu W, Mueller K. Accelerating regularized iterative ct reconstruction on commodity graphics hardware (GPU). In Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009. IEEE Computer Society. 2009. p. 1287-1290. 5193298. (Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009). doi: 10.1109/ISBI.2009.5193298

Accelerating regularized iterative ct reconstruction on commodity graphics hardware (GPU)

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this