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We suggest a symmetric-polar pixellation scheme which makes possible a reduction of the computational cost for expectation maximization (EM) iterative algorithms. The proposed symmetric-polar pixellation allows us to deal with 3D images as a whole problem without dividing the 3D problem into 2D slices approach. Performance evaluation of each approach in(More)
The main technical goal of the MindView project and, thus, the subject of this contribution , is achieving simultaneous PET/MR imaging, dedicated to brain examination in clinical research settings to study psychiatric disorders. The system will allow visualiza-tion of the relevant structures in the brain with very high resolution (~1mm) and sensitivity.(More)
Neural Networks (NNs) have been suggested to fit experimental data in an efficient way when compared to other methods such as least squares fitting. The advantage of NNs is the avoidance of iterative processes and that it does not require initialization parameters. Furthermore, it is possible to implement the network in special purpose hardware, as FPGAs,(More)
In PET detectors based on monolithic scintillators, the photon impact position can be estimated from the light intensity distribution (LD) on the photodetector pixels. Typically, there is a poor estimation of the interaction positions towards the edges when linear algorithms such as Center of Gravity (CoG) are used. We present a novel method to determine(More)
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