Compton camera has great potential in nuclear medicine imaging, and the pre-calculation and evaluation of the point spread function (PSF) and detection efficiency can provide important help for the optimization of the Compton camera systems and the improvement of image reconstruction quality. In this paper, we propose a method for calculating the spatial PSF and detection efficiency of the Compton camera system based on differential transmission probability and GPU acceleration. Different from the existing assumptions based on the uniform distribution of photon action positions in the detector, we consider the changes in the transmission probability at different action positions to obtain a more accurate calculation of the spatial point spread function. Besides, we combine the advantages of GPU parallel computing to divide the calculation of transmission probability into subsets of differential voxels for parallel computing, which greatly improves the calculation speed. The proposed approach could complete the calculation of the detection efficiency in the region of interest of the Compton camera system in about 10 seconds and complete the accurate evaluation of the Compton camera system's spatial PSF within half an hour, with the deviation of less than 1 mm. The rapid estimation of the PSF and the detection efficiency of the Compton camera system obtained by the proposed method could provide the performance estimation and help the optimization of the Compton camera design, and can also improve the accuracy of image reconstruction by using the PSF.
Computed Tomography (CT) has been an irreplaceable method of non-destructive testing in heavy industry and architectural design for a long time. Although, in recent years, a new CT technology with high resolution and extensive applicability for in-situ large-scale structure inspection of concrete has been applied in production. The complexity of the scanning environment and mechanical vibration during the in-situ press loading can result in artifacts on CT image. To solve this problem, a reconstruction algorithm based on system matrix was implemented to reduce of influence caused by track jitter and undefined scanning track. A simulation experiment was performed to verify the algorithm. The result shows the feasibility of the proposed reconstruction algorithm.
KEYWORDS: Head, Monte Carlo methods, In vivo imaging, Cameras, Reconstruction algorithms, Device simulation, Computer simulations, Optical simulations, Gamma ray imaging
Prompt gamma ray (PG) imaging based on Compton camera (CC) has been proposed to realize in vivo verification during the proton therapy. However, due to the inherent geometrical complexity of Compton camera data, PG imaging can be time-consuming and difficult to reconstruct in real-time, while using standard techniques such as filtered back-projection (FBP) or list-mode maximum likelihood-expectation maximization (LM-MLEM). In addition, the imaging quality and spatial resolution of the reconstructed PG images is seriously limited by the finite energy and spatial resolution of CC, as well as the Doppler broaden effect. In this paper, we investigate the performance of in vivo verification via PG imaging with a three-stage Cadmium Zinc Telluride (CZT) pixelated Compton camera during the proton therapy for human head. We demonstrated the real-time PG imaging approach by using Monte Carlo back-projection (MC-BP) and triple events. The prompt gammas were induced by a 69MeV ~ 86 MeV proton pencil beam irradiating the human head phantom, which were simulated by using Geant4 toolkit. The results show that the reconstructions with Compton camera imaging realized nearly real-time PG imaging with a good resolution recovery, as well as provided the accurate estimation of in-vivo verification, thus demonstrating the feasibility in PG-based in-vivo proton range verification with CC.
In order to detect deformations of parts during the operating test, a novel dynamic industry computed tomography (ICT) system taking advantage of the rotation of specimens itself was purposed by us. However the stationary parts such as the shell around the turbine tips, which are hardly removed due to some industrial reasons, contaminate the projection data, so the blocks are not easily corrected from the projections as what we did in the traditional detector correction procedure. In this work, an interaction based CT reconstruction algorithm is purposed to deal the problem. First of all, we directly reconstruct the image with the contaminated projection data and an interactive match between the reconstructed image and the prior image is performed according to some obvious features. Then a forward-projection of the matched prior image with the practical geometric parameters is made. The block components in the projection data are estimated by calculating the average difference between the forward projections and the real projections of certain detectors. Finally, a new image can be reconstructed using the corrected data. Furthermore, the efficiency of the purposed algorithm is proved by both numerical simulation and practical experiments.
Hard X-ray phase-contrast imaging has been a hot research field in the last decade. It can provide high sensitivity of
weakly absorbing low-Z objects in medical and biological fields. Grating-based differential phase-contrast (DPC)
method has been paid more attention to because it can work with conventional X-ray tube and shows great potential for
clinic application. Tomosynthesis with the combination of phase-contrast imaging is considered as a promising imaging
method which can significantly enhance the contrast of low absorbing tissues and eliminate the effects of superimposed
tissue on anatomical structures and is especially useful for medical applications such as mammography. In this paper, an
experimental phase-contrast tomosynthesis system is implemented based on a weakly coherent hard X-ray phase-contrast
method proposed by our group recently. The effectiveness of the proposed method is proved by actual experiments.
Multiple information (absorption, refraction and dark-field) of the samples can be retrieved in one single imaging
process by information retrieving methods. Then tomosynthesis reconstructions can be performed based on the retrieved
information. It can eliminate the overlap of the sample structures and provide more extensive image information
compared with conventional tomosynthesis.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.