@article{ZiemonsBruyndonckxPerezetal.2008,
  author    = {Ziemons, Karl and Bruyndonckx, P. and Perez, J. M. and Pietrzyk, U. and Rato, P. and Tavernier, S.},
  title     = {Beyond ClearPET: Next Aims},
  series = {5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro Symposium Proceedings ISBI 2008},
  journal   = {5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro Symposium Proceedings ISBI 2008},
  isbn      = {978-1-4244-2003-2},
  pages     = {1421 -- 1424},
  year      = {2008},
  abstract  = {The CRYSTAL CLEAR collaboration, in short CCC, is a consortium of 12 academic institutions, mainly from Europe, joining efforts in the area of developing instrumentation for nuclear medicine and medical imaging. In the framework of the CCC a high performance small animal PET system, called ClearPET, was developed by using new technologies in electronics and crystals in a phoswich arrangement combining two types of lutetium- based scintillator materials: LSO:Ce and LuYAP:Ce. Our next aim will be the development of hybrid image systems. Hybrid MR-PET imaging has many unique advantages for brain research. This has sparked a new research line within CCC for the development of novel MR-PET compatible technologies. MRI is not as sensitive as PET but PET has poorer spatial resolution than MRI. Two major advantages of PET are sensitivity and its ability to acquire metabolic information. To assess these innovations, the development of a 9.4T hybrid animal MR-PET scanner is proposed based on an existing 9.4T MR scanner that will be adapted to enable simultaneous acquisition of MR and PET data using cutting- edge technology for both MR and PET.},
  language  = {en}
}
@article{WedrowskiBruyndonckxTavernieretal.2009,
  author    = {Wedrowski, M. and Bruyndonckx, P. and Tavernier, S. and Zhi, L. and Dang, J. and Mendes, P. R. and Perez, J. M. and Ziemons, Karl},
  title     = {Robustness of neural networks algorithm for gamma detection in monolithic block detector, positron emission tomography},
  series = {2009 IEEE Nuclear Science Symposium Conference Record (NSS/MIC)},
  journal   = {2009 IEEE Nuclear Science Symposium Conference Record (NSS/MIC)},
  isbn      = {1082-3654},
  pages     = {2625 -- 2628},
  year      = {2009},
  abstract  = {The monolithic scintillator block approach for gamma detection in the Positron Emission Tomography (PET) avoids estimating Depth of Interaction (DOI), reduces dead zones in detector and diminishes costs of detector production. Neural Networks (NN) are very efficient to determine the entrance point of a gamma incident on a scintillator block. This paper presents results on the robustness of the spatial resolution as a function of the random fraction in the data, temperature and HV fluctuations. This is important when implementing the method in a real scanner. Measurements were done with two Hamamatsu S8550 APD arrays, glued on a 20 {\~A}— 20 {\~A}— 10 mm3 monolithic LSO crystal block.},
  language  = {en}
}