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16 March 2011 New method for tuning hyperparameter for the total variation norm in the maximum a posteriori ordered subsets expectation maximization reconstruction in SPECT myocardial perfusion imaging
Zhaoxia Yang, Andrzej Krol, Yuesheng Xu, David H. Feiglin
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Proceedings Volume 7961, Medical Imaging 2011: Physics of Medical Imaging; 796141 (2011) https://doi.org/10.1117/12.877796
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States
Abstract
In order to improve the tradeoff between noise and bias, and to improve uniformity of the reconstructed myocardium while preserving spatial resolution in parallel-beam collimator SPECT myocardial perfusion imaging (MPI) we investigated the most advantageous approach to provide reliable estimate of the optimal value of hyperparameter for the Total Variation (TV) norm in the iterative Bayesian Maximum A Posteriori Ordered Subsets Expectation Maximization (MAP-OSEM) one step late tomographic reconstruction with Gibbs prior. Our aim was to find the optimal value of hyperparameter corresponding to the lowest bias at the lowest noise while maximizing uniformity and spatial resolution for the reconstructed myocardium in SPECT MPI. We found that the L-curve method that is by definition a global technique provides good guidance for selection of the optimal value of the hyperparameter. However, for a heterogeneous object such as human thorax the fine-tuning of the hyperparameter's value can be only accomplished by means of a local method such as the proposed bias-noise distance (BND) curve. We established that our BND-curve method provides accurate optimized hyperparameter's value estimation as long as the region of interest volume for which it is defined is sufficiently large and is located sufficiently close to the myocardium.
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Zhaoxia Yang, Andrzej Krol, Yuesheng Xu, and David H. Feiglin "New method for tuning hyperparameter for the total variation norm in the maximum a posteriori ordered subsets expectation maximization reconstruction in SPECT myocardial perfusion imaging", Proc. SPIE 7961, Medical Imaging 2011: Physics of Medical Imaging, 796141 (16 March 2011); https://doi.org/10.1117/12.877796
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KEYWORDS
Single photon emission computed tomography
Lung
Monte Carlo methods
Spatial resolution
Signal to noise ratio
Collimators
Image quality
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