Sampling conditions for gradient-magnitude sparsity based image reconstruction algorithms

Emil Y. Sidky; Jakob Heide Jørgensen; Xiaochuan Pan

doi:10.1117/12.913307

Sampling conditions for gradient-magnitude sparsity based image reconstruction algorithms

Emil Y. Sidky, Jakob Heide Jørgensen, Xiaochuan Pan

Research output: Contribution to journal › Conference article › Research › peer-review

Abstract

We seek to characterize the sampling conditions for iterative image reconstruction exploiting gradient-magnitude sparsity. We seek the number of views necessary for accurate image reconstruction by constrained, total variation (TV) minimization, which is the optimization problem suggested in the compressive sensing (CS) community for this type of sparsity. The preliminary finding here, based on simulations using images of realistic sparsity levels, is that necessary sampling can go as low as N/4 views for an NxN pixel array. This work sets the stage for fixed-exposure studies where the number of projections is balanced against the X-ray intensity per projection.

Original language	English
Journal	Proceedings of SPIE, the International Society for Optical Engineering
Volume	8313
Pages (from-to)	8313-116
ISSN	0277-786X
DOIs	https://doi.org/10.1117/12.913307
Publication status	Published - 2012
Event	SPIE Medical Imaging 2012: Ultrasonic Imaging, Tomography, and Therapy - San Diego, United States Duration: 4 Feb 2012 → 9 Feb 2012

Conference

Conference	SPIE Medical Imaging 2012
Country/Territory	United States
City	San Diego
Period	04/02/2012 → 09/02/2012
Other	Proc. volume 8320

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title = "Sampling conditions for gradient-magnitude sparsity based image reconstruction algorithms",

abstract = "We seek to characterize the sampling conditions for iterative image reconstruction exploiting gradient-magnitude sparsity. We seek the number of views necessary for accurate image reconstruction by constrained, total variation (TV) minimization, which is the optimization problem suggested in the compressive sensing (CS) community for this type of sparsity. The preliminary finding here, based on simulations using images of realistic sparsity levels, is that necessary sampling can go as low as N/4 views for an NxN pixel array. This work sets the stage for fixed-exposure studies where the number of projections is balanced against the X-ray intensity per projection.",

author = "Sidky, {Emil Y.} and J{\o}rgensen, {Jakob Heide} and Xiaochuan Pan",

year = "2012",

doi = "10.1117/12.913307",

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pages = "8313--116",

journal = "Proceedings of SPIE, the International Society for Optical Engineering",

issn = "0277-786X",

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note = "SPIE Medical Imaging 2012 : Ultrasonic Imaging, Tomography, and Therapy ; Conference date: 04-02-2012 Through 09-02-2012",

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T1 - Sampling conditions for gradient-magnitude sparsity based image reconstruction algorithms

AU - Sidky, Emil Y.

AU - Jørgensen, Jakob Heide

AU - Pan, Xiaochuan

PY - 2012

Y1 - 2012

N2 - We seek to characterize the sampling conditions for iterative image reconstruction exploiting gradient-magnitude sparsity. We seek the number of views necessary for accurate image reconstruction by constrained, total variation (TV) minimization, which is the optimization problem suggested in the compressive sensing (CS) community for this type of sparsity. The preliminary finding here, based on simulations using images of realistic sparsity levels, is that necessary sampling can go as low as N/4 views for an NxN pixel array. This work sets the stage for fixed-exposure studies where the number of projections is balanced against the X-ray intensity per projection.

AB - We seek to characterize the sampling conditions for iterative image reconstruction exploiting gradient-magnitude sparsity. We seek the number of views necessary for accurate image reconstruction by constrained, total variation (TV) minimization, which is the optimization problem suggested in the compressive sensing (CS) community for this type of sparsity. The preliminary finding here, based on simulations using images of realistic sparsity levels, is that necessary sampling can go as low as N/4 views for an NxN pixel array. This work sets the stage for fixed-exposure studies where the number of projections is balanced against the X-ray intensity per projection.

U2 - 10.1117/12.913307

DO - 10.1117/12.913307

M3 - Conference article

VL - 8313

SP - 8313

EP - 8116

JO - Proceedings of SPIE, the International Society for Optical Engineering

JF - Proceedings of SPIE, the International Society for Optical Engineering

SN - 0277-786X

T2 - SPIE Medical Imaging 2012

Y2 - 4 February 2012 through 9 February 2012

ER -

Sampling conditions for gradient-magnitude sparsity based image reconstruction algorithms

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