This paper is focused on discrete scintillation imaging devices, made by using crystal arrays and metal-channel dynode Hamamatsu 1" and 2" square position sensitive photomultiplier tubes (PSPMT). These devices are particularly suitable for nuclear medicine based high-resolution Single Photon Emission Computed Tomography (SPECT) applications. A more adequate analytical model describing the light-output spread from a single crystal-pixel, was studied. Previously experimental data published by us were reviewed using this model. The parameter which describes the intrinsic pixel light-output spread was obtained using a 1D model-version, that adequately fits the measured single-event charge-strip integrals. Furthermore the intrinsic spread was found linearly dependent, in the examined experiments, on a crystal-pixel shape factor (defined as the ratio between the pixel-blind-surface-area to the pixel-volume). Finally, a simulation tool was developed on these basis, to predict and to optimize the imager response by evaluating the impact of each device component on the response.
A study of intrinsic crystal-pixel light-output spread for discrete scintillation gamma-ray imagers modeling
Soluri A;
2002
Abstract
This paper is focused on discrete scintillation imaging devices, made by using crystal arrays and metal-channel dynode Hamamatsu 1" and 2" square position sensitive photomultiplier tubes (PSPMT). These devices are particularly suitable for nuclear medicine based high-resolution Single Photon Emission Computed Tomography (SPECT) applications. A more adequate analytical model describing the light-output spread from a single crystal-pixel, was studied. Previously experimental data published by us were reviewed using this model. The parameter which describes the intrinsic pixel light-output spread was obtained using a 1D model-version, that adequately fits the measured single-event charge-strip integrals. Furthermore the intrinsic spread was found linearly dependent, in the examined experiments, on a crystal-pixel shape factor (defined as the ratio between the pixel-blind-surface-area to the pixel-volume). Finally, a simulation tool was developed on these basis, to predict and to optimize the imager response by evaluating the impact of each device component on the response.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


