One of the main factors in the cost of PET scanners is the scintillator crystals used to detect the 511 keV gamma photons emitted from positron annihilations. Conventional PET systems utilise huge numbers of tiny individual crystals, with complex light-sharing schemes needed to obtain depth of interaction (DOI) information. While monolithic scintillators offer a simpler alternative to discrete crystal PET, large single-crystal scintillators with uniform optical properties are both expensive and difficult to fabricate in non-planar geometries. Two new classes of scintillator materials – nanocomposites and transparent polycrystalline ceramics – can potentially enable fabrication of high quality monolithic scintillator blocks in non-planar geometries, at a substantially lower cost compared to conventional scintillator materials. However, due to their inferior optical properties, a number of performance trade-offs must be considered in the design of position-sensitive detectors based on these materials. In this presentation, I will describe an optimisation method which can be applied to the design of monolithic nanocomposite and transparent ceramic scintillator slabs, and present some initial results for a PET scanner design which exploits these capabilities.
Speaker: Dr. Daniel Franklin, Univ. Tech. Sydney
Time: 15:30, Tuesday, October 27, 2020
Venue: G2-315, 144 Xuan Thuy, Cau Giay, Hanoi
Daniel Franklin received his Bachelor of Engineering (Electrical, Honours I) and Ph.D. in Telecommunications Engineering from the University of Wollongong, Wollongong, Australia, in 1999 and 2007, respectively. He is currently a Senior Lecturer with the School of Electrical and Data Engineering at the University of Technology Sydney, Australia. His current research and commercial interests include positron emission tomography, computed tomography, particle therapy, image and multimedia signal processing and analysis, wireless telecommunications systems, telemetry and telecontrol systems, and quality of experience in telecommunications networks.