Learning SPECT detector response for Monte-Carlo simulations
Résumé
The use of Artificial Neural Networks (ANN) was investigated to learn detector response in Monte-Carlo (MC) simulation of imaging systems in order to replace computationally costly particle tracking in the detector. The proposed method is applied to speed-up simulation of collimator-detector systems with Angular Response Function (ARF) for SPECT imaging.
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