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Within the Crystal Clear Collaboration a modular system for a small animal PET scanner (ClearPET™) has been developed. The modularity allows the assembly of scanners of different sizes and characteristics in order to fit the specific needs of the individual member institutions. Now a first demonstrator is being completed in Julich. The system performs depth of interaction detection by using a phoswich arrangement combining LSO and LuYAP scintillators which are coupled to multi-channel photomultipliers (PMTs). A free-running ADC digitizes the signal from the PMT and the complete scintillation pulses are sampled by an FPGA and sent with 20 MB/S to a PC for preprocessing. The pulse provides information about the gamma energy and the scintillator material which identifies the interaction layer. Furthermore, the exact pulse starting time is obtained from the sampled data. This is important as no hardware coincidence detection is implemented. All single events are recorded and coincidences are identified by software. An advantage of that is that the coincidence window and the dimensions of the field of view can be adjusted easily. The ClearPET™ demonstrator is equipped with 10240 crystals on 80 PMTs. This paper presents an overview of the data acquisition system.
MultiChannel Photomultipliers (PM), like the R7600-00-M64 or R5900-00-M64 from Hamamatsu, are often chosen as photodetectors in high-resolution positron emission tomography (PET). A major problem of this PM is the nonuniform channel gain. In order to solve this problem, light attenuating masks were created. The aim of the masks is a homogenization of the output of all 64 channels using different hole sizes at the channel positions. The hole area, which is individually defined for the different channels, is inversely proportional to the channel gain. The measurements by inserting light attenuating masks improved a homogenization to a ratio of 1:1.2.
This paper examines the positive and negative aspects of a range of interpretations of nearest-neighbours models. Measures-oriented and distributionoriented verification methods are applied to categorial, probabilistic and descriptive interpretations of nearest neighbours used operationally in avalanche forecasting in Scotland and Switzerland. The dependence of skill and accuracy measures on base rate is illustrated. The purpose of the forecast and the definition of events are important variables in determining the quality of the forecast. A discussion of the application of different interpretations in operational avalanche forecasting is presented.