1996
DOI: 10.1007/978-94-015-8749-5_11
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Characteristics of Reconstructed Point Response in three-Dimensional Spatially Variant Detector Response Compensation in SPECT

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Cited by 14 publications
(7 citation statements)
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“…The number of updates was set at 210 (210 iterations for ML-EM and 10 iterations with 21 subsets for OS-EM) to avoid possible nonconvergent bias. 13 Partial volume correction using the known phantom image was applied to the reconstructed activity in the aorta. The bias of ML-EM and OS-EM methods was calculated using the averaged results of 100 different noise realizations.…”
Section: D Effects Of Different Reconstruction Methodsmentioning
confidence: 99%
“…The number of updates was set at 210 (210 iterations for ML-EM and 10 iterations with 21 subsets for OS-EM) to avoid possible nonconvergent bias. 13 Partial volume correction using the known phantom image was applied to the reconstructed activity in the aorta. The bias of ML-EM and OS-EM methods was calculated using the averaged results of 100 different noise realizations.…”
Section: D Effects Of Different Reconstruction Methodsmentioning
confidence: 99%
“…It is thereby a means to compensate for the collimator-detector response (CDR) in iterative reconstruction. [78][79][80] The CDR consists of four main components: intrinsic response (the system without a collimator) and the geometric, septal penetration, and septal scatter components of the collimator parameters. By including an accurate model of CDR function in an iterative SPECT reconstruction algorithm, compensation for the blurring effect may be included in the iterative reconstruction process, resulting in improved spatial resolution and a reduction in image noise.…”
Section: Filteredmentioning
confidence: 99%
“…Let represent the activity in these coordinates, and denote by the noise-free projection associated with a point on the detector. These projections are characterized by the attenuation and detector response according to the relation (2) with the attenuation factor for a source at and the Gaussian detector PSF (3) modeling isotropic blurring in and with a standard deviation (in centimeters) of . This PSF is equal to the convolution of a Gaussian having a constant standard deviation with a Gaussian having a distance-dependent standard deviation of , where is the perpendicular distance from the source to the detector face.…”
Section: B Data Generationmentioning
confidence: 99%
“…The detector point spread function (PSF) that describes the acquisition of primary photons with a parallel-hole collimator can be approximated by a two-dimensional (2-D) Gaussian whose full-width at half-maximum (FWHM) increases linearly with the source-to-detector distance [2]. This distance-dependent resolution in the data leads to nonstationary blurring of reconstructed images [3]. A number of methods (e.g., [4]- [13]) have been proposed for detector-response compensation (DRC).…”
Section: Introductionmentioning
confidence: 99%