Super-resolution acquisition and reconstruction for cone-beam SPECT with low-resolution detector. (April 2022)

• Record Type: Journal Article
• Authors: Cheng, Zhibiao; Xie, Lulu; Feng, Cuixia; Wen, Junhai
• Is Part Of: Computer methods and programs in biomedicine. Volume 217(2022)
• Publication Date: 2022-04
• Subjects: Super resolution -- Cone-beam -- SPECT -- Rotation; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2022.106683
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: Novel super resolution reconstruction algorithm for cone-beam SPECT with low resolution detector. Two low resolution projection acquisition schemes are designed for cone-beam SPECT. Method does not require high resolution detectors, but only one or more low resolution detectors. Simulation result means that the resolution of the SPECT image is almost four times higher. Abstract: Background and objective: Single-photon emission computed tomography (SPECT) imaging, which provides information that reflects the human body's metabolic processes, has unique application value in disease diagnosis and efficacy evaluation. The imaging resolution of SPECT can be improved by exploiting high-performance detector hardware, but this exploitation generates high research and development costs. In addition, the inherent hardware structure of SPECT requires the use of a collimator, which limits the resolution in SPECT. The objective of this study is to propose a novel super-resolution (SR) reconstruction algorithm with two acquisition methods for cone-beam SPECT with low-resolution (LR) detector. Methods: A SR algorithm with two acquisition methods is proposed for cone-beam SPECT imaging in the projection domain. At each sampling angle, multi LR projections can be obtained by regularly moving the LR detector. For the two proposed acquisition methods, we develop a new SR reconstruction algorithm. Using our SR algorithm, a SR projection with the corresponding sampling angle can be obtained from multi LR projections via multi-iterations, and then, the SR SPECT image can be reconstructed. The peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), signal-to-noise ratio (SNR) and contrast recovery coefficient (CRC) are used to evaluate the final reconstruction quality. Results: The simulation results obtained under clean and noisy conditions verify the effectiveness of our SR algorithm. Three different phantoms are verified separately. 16 LR projections are obtained at each sampling angle, each with 32 × 32 bins. The high-resolution (HR) projection has 128 × 128 bins. The reconstruction result of the SR algorithm obtains an evaluation value that is almost the same as that of the HR reconstruction result. Our results indicate that the resolution of the resulting SPECT image is almost four times higher. Conclusions: The authors develop a SR reconstruction algorithm with two acquisition methods for the cone-beam SPECT system. The simulation results obtained in clean and noisy environments prove that the SR algorithm has potential value, but it needs to be further tested on real equipment.