An optimal rotator for iterative reconstruction

Wallis, Jerold W.; Miller, Tom R.

doi:10.1109/42.552061

Cited by 55 publications

(44 citation statements)

References 12 publications

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“…Arbitrary projection angles can be placed in this orientation by appropriately rotating the estimated emission voxel slices and attenuation maps. 29 Given an aligned attenuation map for an estimate of an emission slice, one could include attenuation by starting with the voxel on the side opposite the projection being created and multiplying its value by the TF for passing through one-half the voxel distance of an attenuator of the given attenuation coefficient. The value of one-half the pixel dimension is usually used as an approximation for the self-attenuation of the activity in the voxel.…”

Section: Backproject Ratios For Allmentioning

confidence: 99%

An Overview of Attenuation and Scatter Correction of Planar and SPECT Data for Dosimetry Studies

King

Farncombe²

2003

Cancer Biotherapy and Radiopharmaceuticals

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A number of factors impact the accuracy of activity quantitation in planar and single photon emission computed tomographic (SPECT) imaging. Two important such factors are attenuation and scattering in the medium containing the activity. The first removes photons which otherwise would have been included in the images, and the second adds events to the images from photons which would not have otherwise been imaged. A number of methods have been developed to compensate for these biases to activity quantitation. This review will briefly introduce planar quantitation which is commonly used for dosimeter purposes, and then present a slightly more detailed overview of SPECT quantitation which is arguably more accurate. It will conclude by cautioning users of commercial reconstruction software to validate it for quantitation before using it for dosimetric purposes.

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Section: Backproject Ratios For Allmentioning

confidence: 99%

An Overview of Attenuation and Scatter Correction of Planar and SPECT Data for Dosimetry Studies

King

Farncombe²

2003

Cancer Biotherapy and Radiopharmaceuticals

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“…We propose use of three-dimensional (3D) Gaussian interpolation to provide the interpolation required in these steps. Twodimensional (2D) Gaussian interpolation is widely used in iterative reconstruction because of its outstanding properties as a slice rotator [20]. It rotates a slice of the image grid (2D coordinate system) to be aligned with the camera head.…”

Section: Introductionmentioning

confidence: 99%

Use of three-dimensional Gaussian interpolation in the projector/backprojector pair of iterative reconstruction for compensation of known rigid-body motion in SPECT

Feng

Gifford

Beach

et al. 2006

IEEE Trans. Med. Imaging

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Due to the extended imaging times employed in SPECT and PET, patient motion during imaging is a common clinical occurrence. The fast and accurate correction of the three-dimensional (3D) translational and rotational patient motion in iterative reconstruction is thus necessary to address this important cause of artifacts. We propose a method of incorporating 3D Gaussian interpolation in the projector/backprojector pair to facilitate compensation for rigid-body motion in addition to attenuation and distance-dependent blurring. The method works as the interpolation step for moving the current emission voxel estimates and attenuation maps in the global coordinate system to the new patient location in the rotating coordinate system when calculating the expected projection. It also is employed for moving back the backprojection of the ratio of the measured projection to the expected projection and backprojection of the unit value (sensitivity factor) to the original location. MCAT simulations with known six-degree-of-freedom (6DOF) motion were employed to evaluate the accuracy of our method of motion compensation. We also tested the method with acquisitions of the Data Spectrum Anthropomorphic phantom where motion during SPECT acquisition was measured using the Polaris IR motion tracking system. No motion artifacts were seen on the reconstructions with the motion compensation.

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“…Notice that and can be derived from each other through rotation [29][30][31] and can be calculated by (22). Define , we derive the expression of (7) in the coordinate (s,t) θ k as: (24) Similarly we have under (s,t) θ k .…”

Section: A Phantoms and Implementation Of The Ml-em Algorithmmentioning

confidence: 99%

Range Condition and ML-EM Checkerboard Artifacts

You

Wang

Zhang

2007

IEEE Trans. Nucl. Sci.

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The expectation maximization (EM) algorithm for the maximum likelihood (ML) image reconstruction criterion generates severe checkerboard artifacts in the presence of noise. A classical remedy is to impose an a priori constraint for a penalized ML or maximum a posteriori probability solution. The penalty reduces the checkerboard artifacts and also introduces uncertainty because a priori information is usually unknown in clinic. Recent theoretical investigation reveals that the noise can be divided into two components: one is called null-space noise and the other is range-space noise. The null-space noise can be numerically estimated using filtered backprojection (FBP) algorithm. By the FBP algorithm, the null-space noise annihilates in the reconstruction while the range-space noise propagates into the reconstructed image. The aim of this work is to investigate the relation between the null-space noise and the checkerboard artifacts in the ML-EM reconstruction from noisy projection data. Our study suggests that removing the null-space noise from the projection data could improve the signal-to-noise ratio of the projection data and, therefore, reduce the checkerboard artifacts in the ML-EM reconstructed images. This study reveals an in-depth understanding of the different noise propagations in analytical and iterative image reconstructions, which may be useful to single photon emission computed tomography, where the noise has been a major factor for image degradation. The reduction of the ML-EM checkerboard artifacts by removing the null-space noise avoids the uncertainty of using a priori penalty.

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An optimal rotator for iterative reconstruction

Cited by 55 publications

References 12 publications

An Overview of Attenuation and Scatter Correction of Planar and SPECT Data for Dosimetry Studies

An Overview of Attenuation and Scatter Correction of Planar and SPECT Data for Dosimetry Studies

Use of three-dimensional Gaussian interpolation in the projector/backprojector pair of iterative reconstruction for compensation of known rigid-body motion in SPECT

Range Condition and ML-EM Checkerboard Artifacts

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