###### System matrix computation for iterative reconstruction algorithms in SPECT based on direct measurements

## System matrix computation for iterative reconstruction algorithms in SPECT based on direct measurements

A method for system matrix calculation in the case of iterative reconstruction algorithms in SPECT was implemented and tested. Due to a complex mathematical description of the geometry of the detector set-up, we developed a method for system matrix computation that is based on direct measurements of the detector response. In this approach, the influence of the acquisition equipment on the image formation is measured directly. The objective was to obtain the best quality of reconstructed images with respect to specified measures. This is indispensable in order to be able to perform reliable quantitative analysis of SPECT images. It is also especially important in non-hybrid gamma cameras, where not all physical processes that disturb image acquisition can be easily corrected. Two experiments with an ^{131}
*I* point source placed at different distances from the detector plane were performed allowing the detector response to be acquired as a function of the point source distance. An analytical Gaussian function was fitted to the acquired data in both the one- and the two-dimensional case. A cylindrical phantom filled with a water solution of ^{131}
*I* containing a region of "cold" spheres as well as a uniform solution (without any spheres) was used to perform algorithm evaluation. The reconstructed images obtained by using four different of methods system matrix computation were compared with those achieved using reconstruction software implemented in the gamma camera. The contrast of the spheres and uniformity were compared for each reconstruction result and also with the ranges of those values formulated by the AAPM (American Association of Physicists in Medicine). The results show that the implementation of the OSEM (Ordered Subsets Expectation Maximization) algorithm with a one-dimensional fit to the Gaussian CDR (Collimator-Detector Response) function provides the best results in terms of adopted measures. However, the fit of the two-dimensional function also gives satisfactory results. Furthermore, the CDR function has the potential to be applied to a fully 3D OSEM implementation. The lack of the CDR in system matrix calculation results in a very noisy image that cannot be used for diagnostic purposes.

###### IoT Sensing Networks for Gait Velocity Measurement

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###### New stability conditions for positive continuous-discrete 2D linear systems

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###### A new sufficient schedulability analysis for hybrid scheduling

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###### Computer methods for stability analysis of the Roesser type model of 2D continuous-discrete linear systems

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###### Stochastic Fractal Based Multiobjective Fruit Fly Optimization

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###### Machine learning techniques combined with dose profiles indicate radiation response biomarkers

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###### Design of unknown input fractional-order observers for fractional-order systems

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###### Sensor network design for the estimation of spatially distributed processes

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###### QSPR Analysis of certain Distance Based Topological Indices

is that the structural characteristics of a molecule are responsible for its properties. Topological indices are a convenient means of translating chemical constitution into numerical values which can be used for correlation with physical properties in quantitative structure-property/activity relationship (QSPR/QSAR) studies. The use of graph invariant (topological indices) in QSPR and QSAR studies has become of major interest in recent years. Topological indices have found application in various areas of chemistry, physics, mathematics, informatics, biology, etc