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Title: A Bayesian iterative transmission gradient reconstruction algorithm for cardiac SPECT attenuation correction
Authors: Case JA
Hsu BL
Bateman TM
Cullom SJ
Contributors: 國立臺灣海洋大學:資訊工程學系
Keywords: Single photon emission computed tomography
myocardial perfusion
attenuation correction
iterative reconstruction
Date: 2007-05
Issue Date: 2018-11-15T03:33:02Z
Publisher: Journal of nuclear cardiology
Abstract: Abstract: Background:
High-quality attenuation maps are critical for attenuation correction of myocardial perfusion single photon emission computed tomography studies. The filtered backprojection (FBP) approach can introduce errors, especially with low-count transmission data. We present a new method for attenuation map reconstruction and examine its performance in phantom and patient data.

The Bayesian iterative transmission gradient algorithm incorporates a spatially varying gamma prior function that preferentially weights estimated attenuation coefficients toward the soft-tissue value while allowing data-driven solutions for lung and bone regions. The performance with attenuation-corrected technetium 99m sestamibi clinical images was evaluated in phantom studies and in 50 low-likelihood patients grouped by body mass index (BMI). The algorithm converged in 15 iterations in the phantom studies. For the clinical studies, soft-tissue estimates had significantly greater uniformity of mediastinal coefficients (mean SD, 0.005 cm(-1) vs 0.011 cm(-1); P < .0001). The accuracy and uniformity of the Bayesian iterative transmission gradient algorithm were independent of BMI, whereas both declined at higher BMI values with FBP. Attenuation-corrected perfusion images showed improvement in myocardial wall variability (4.8% to 4.1%, P = .02) for all BMI groups with the new method compared with FBP.

This new method for attenuation map reconstruction provides rapidly converging and accurate attenuation maps over a wide spectrum of patient BMI values and significantly improves attenuation-corrected perfusion images.
Relation: 14(3) pp.324-333
Appears in Collections:[Department of Computer Science and Engineering] Periodical Articles

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