Abstract
Null functions of an imaging system are functions in the object space that give exactly zero data. Hence, they represent the intrinsic limitations of the imaging system. Null functions exist in all digital imaging systems, because these systems map continuous objects to discrete data. However, the emergence of detectors that measure continuous data, e.g. particle-processing (PP) detectors, has the potential to eliminate null functions. PP detectors process signals produced by each particle and estimate particle attributes, which include two position coordinates and three components of momentum, as continuous variables. We consider Charged-Particle Emission Tomography (CPET), which relies on data collected by a PP detector to reconstruct the 3D distribution of a radioisotope that emits alpha or beta particles, and show empirically that the null functions are significantly reduced for alpha particles if ≥3 attributes are measured or for beta particles with five attributes measured.
Highlights
Null functions of an imaging system are functions in the object space that give exactly zero data
Our results show that the null functions are significantly reduced for alpha particles with q ≥ 3 or for beta particles with q = 5, where q is the number of attributes estimated for each particle
We have demonstrated the potential of particle-processing (PP) detectors in reducing null functions of Charged-Particle Emission Tomography (CPET)
Summary
Null functions of an imaging system are functions in the object space that give exactly zero data. They represent the intrinsic limitations of the imaging system. Null functions exist in all digital imaging systems, because these systems map continuous objects to discrete data. The emergence of detectors that measure continuous data, e.g. particle-processing (PP) detectors, has the potential to eliminate null functions. PP detectors process signals produced by each particle and estimate particle attributes, which include two position coordinates and three components of momentum, as continuous variables. Recent work[9] has shown that null functions can be reduced if continuous data are collected instead of discrete data for Single Photon Emission Computed Tomography (SPECT). The continuous data are collected with photon-processing detectors[10,11,12,13,14,15,16] that apply a maximum-likelihood[11,13,17,18,19,20] method to estimate the interaction position, deposited energy and other attributes of each photon-interaction event
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
