Year: 2018
Type: book-chapter
Abstract: We present computational methods for attribute estimation of photon-counting and photon-processing detectors. We define a photon-processing detector as any imaging device that uses maximum-likelihood methods to estimate photon attributes, such as position, direction of propagation and energy. Estimated attributes are then stored at full precision in the memory of a computer. Accurate estimation of a large number of attributes for each collected photon does require considerable computational power. We show how mass-produced graphics processing units (GPUs) are viable parallel computing solutions capable of meeting the required computing needs of photon-counting and photon-processing detectors, while keeping overall costs affordable.
Source: InTech eBooks
Authors: Luca Caucci, Yijun Ding, Harrison H. Barrett
Institutions: University of Arizona, University of Colorado Denver
Language: English
Subfield: Radiation
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2793250650