14 research outputs found

    Application of reconstruction-based scatter compensation to thallium-201 SPECT: implementations for reduced reconstructed image noise

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    Scatter compensation in Tl-201 single photon emission computed tomography (SPECT) presents an interesting challenge because of the multiple emission energies and relatively large proportion of scattered photons. In this paper, we present a simulation study investigating reconstructed image noise levels arising from various implementations of iterative reconstruction-based scatter compensation (RBSC) in Tl-201 SPECT. A two-stage analysis was used to study single and multiple energy window implementations of reconstruction-based scatter compensation, and RBSC was compared to the upper limits on performance for other approaches to handling scatter. In the first stage, singular value decomposition of the system transfer matrix was used to analyze noise levels in a manner independent of the choice of reconstruction algorithm, providing results valid across a wide range of regularizations. In the second stage, the data were reconstructed using maximum-likelihood expectation-maximization, and the noise properties of the resultant images were analyzed. The best RBSC performance was obtained using multiple energy windows, one for each emission photopeak, and RBSC outperformed the upper limit on subtraction-based compensation methods. Implementing RBSC with the correct choice of energy window acquisition scheme is a promising method for performing scatter compensation for Tl-201 SPECT

    An SVD investigation of modeling scatter in multiple energy windows for improved SPECT images

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    In this work singular value decomposition (SVD) techniques are used to investigate how the use of low energy photons and multiple energy windows affects the noise properties of Tc-99m SPECT imaging. We have previously shown that, when modeling scatter in the projector and backprojector of iterative reconstruction algorithms, simultaneous reconstruction from multiple energy window data can result in very different noise characteristics. Further, the properties depend upon the width and number of energy windows used. To investigate this further, we have generated photon transport matrices using models for scatter, an elliptical phantom containing cold rods of various sizes, and a number of multiple energy window acquisition schemes. Transfer matrices were also generated for the cases of perfect scatter rejection and ideal scatter subtraction. The matrices were decomposed using SVD, and signal power and projection space variance spectra were computed using the basis formed by the left singular vectors. Results indicate very different noise levels for the various energy window combinations. The perfect scatter rejection case resulted in the lowest variance spectrum, and reconstruction-based scatter compensation performed better than the scatter subtraction case. When including lower energy photons in reconstruction-based scatter compensation, using a series of multiple energy windows outperformed a single large energy window. One multiple window combination is presented which achieves a lower variance spectrum than the standard 20% energy window, indicating the potential for using low energy photons to improve the noise characteristics of SPECT images

    Electronic Noise Modeling in Statistical Iterative Reconstruction

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    Advances in computational human phantoms and their applications in biomedical engineering - A topical review.

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    Over the past decades, significant improvements have been made in the field of computational human phantoms (CHPs) and their applications in biomedical engineering. Their sophistication has dramatically increased. The very first CHPs were composed of simple geometric volumes, e.g., cylinders and spheres, while current CHPs have a high resolution, cover a substantial range of the patient population, have high anatomical accuracy, are poseable, morphable, and are augmented with various details to perform functionalized computations. Advances in imaging techniques and semi-automated segmentation tools allow fast and personalized development of CHPs. These advances open the door to quickly develop personalized CHPs, inherently including the disease of the patient. Because many of these CHPs are increasingly providing data for regulatory submissions of various medical devices, the validity, anatomical accuracy, and availability to cover the entire patient population is of utmost importance. The article is organized into two main sections: the first section reviews the different modeling techniques used to create CHPs, whereas the second section discusses various applications of CHPs in biomedical engineering. Each topic gives an overview, a brief history, recent developments, and an outlook into the future
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