A simultaneous beta and coincidence-gamma imaging system for plant leaves. (13th April 2016)

• Record Type: Journal Article
• Authors: Ranjbar, Homayoon; Wen, Jie; Mathews, Aswin J; Komarov, Sergey; Wang, Qiang; Li, Ke; O'Sullivan, Joseph A; Tai, Yuan-Chuan
• Is Part Of: Physics in medicine & biology. Volume 61:Number 9(2016:May)
• Page Start: 3572
• Page End: 3595
• Publication Date: 2016-04-13
• Subjects: positron -- coincidence-gamma -- joint estimation -- structural similarity -- quantitative imaging -- plant leaf -- simultaneous detection; Biophysics -- Periodicals; Medical physics -- Periodicals; 610.153
• DOI: 10.1088/0031-9155/61/9/3572
• Languages: English
• ISSNs: 0031-9155

Abstract

Abstract: Positron emitting isotopes, such as 11 C, 13 N, and 18 F, can be used to label molecules. The tracers, such as 11 CO2, are delivered to plants to study their biological processes, particularly metabolism and photosynthesis, which may contribute to the development of plants that have a higher yield of crops and biomass. Measurements and resulting images from PET scanners are not quantitative in young plant structures or in plant leaves due to poor positron annihilation in thin objects. To address this problem we have designed, assembled, modeled, and tested a nuclear imaging system (simultaneous beta–gamma imager). The imager can simultaneously detect positrons ( β + ) and coincidence-gamma rays ( γ ). The imaging system employs two planar detectors; one is a regular gamma detector which has a LYSO crystal array, and the other is a phoswich detector which has an additional BC-404 plastic scintillator for beta detection. A forward model for positrons is proposed along with a joint image reconstruction formulation to utilize the beta and coincidence-gamma measurements for estimating radioactivity distribution in plant leaves. The joint reconstruction algorithm first reconstructs beta and gamma images independently to estimate the thickness component of the beta forward model and afterward jointly estimates the radioactivity distribution in the object. We have validated the physics model and reconstruction framework through a phantom imaging study and imaging a tomato leaf that has absorbed 11 CO2 . The results demonstrate that the simultaneously acquired beta and coincidence-gamma data, combined with our proposed joint reconstruction algorithm, improved the quantitative accuracy of estimating radioactivity distribution in thin objects such as leaves. We used the structural similarity (SSIM) index for comparing the leaf images from the simultaneous beta–gamma imager with the ground truth image. The jointly reconstructed images yield SSIM indices of 0.69 and 0.63, whereas the separately reconstructed beta alone and gamma alone images had indices of 0.33 and 0.52, respectively.