- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Study of Sensitivity and Resolution for Full Ring PET Prototypes based on Continuous Crystals and analytical modeling of the light distribution
摘要： Sensitivity and spatial resolution are the main parameters to maximize in the performance of a PET scanner. For this purpose, detectors consisting of a combination of continuous crystals optically coupled to segmented photodetectors have been employed. With the use of continuous crystals the sensitivity is increased with respect to the pixelated crystals. In addition, spatial resolution is no longer limited to the crystal size. The main drawback is the difficulty in determining the interaction position. In this work, we present the characterization of the performance of a full ring based on cuboid continuous crystals coupled to SiPMs. To this end, we have employed the simulations developed in a previous work for our experimental detector head. Sensitivity could be further enhanced by using tapered crystals. This enhancement is obtained by increasing the solid angle coverage, reducing the wedge-shaped gaps between contiguous detectors. The performance of the scanners based on both crystal geometries was characterized following NEMA NU 4-2008 standardized protocol in order to compare them. An average sensitivity gain over the entire axial field of view of 13.63% has been obtained with tapered geometry while similar performance of the spatial resolution has been proven with both scanners. The activity at which NECR and True peak occur is smaller and the peak value is greater for tapered crystals than for cuboid crystals. Moreover, a higher degree of homogeneity was obtained in the sensitivity map due to the tighter packing of the crystals, which reduces the gaps and results in a better recovery of homogeneous regions than for the cuboid configuration. Some of the results obtained, such as spatial resolution, depend on the interaction position estimation and may vary if other method is employed.
关键词： NEMA NU 4-2008,Monte Carlo simulations,image reconstruction,continuous crystals,depth of interaction,positron emission tomography (PET)
更新于2025-09-04 15:30:14
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Image reconstruction for frequency-domain diffuse optical tomography
摘要： The image reconstruction algorithm of diffuse optical tomography (DOT) is based on the diffusion equation and involves both the forward problem and inverse solution. The forward problem solves the diffusion equation using the finite element method for calculating the transmitted light distribution under the condition of presumed light source and optical coefficient. The inverse solution reconstructs the optical property coefficient distribution using Newton’s method. The work within this study develops an image reconstruction algorithm for frequency-domain DOT. A numerical simulations approach to light propagation in the tissue is conducted, while the optical property is reconstructed employing data around the boundary. We implement different designated simulation cases, including different contrast ratios of absorption and reduced scattering coefficient of inclusion with respect to the background used for verifying the results of the forward problem and the developed reconstruction algorithm. Reconstruction results indicate that the quality of reconstructed images can be effective for screening breast cancer.
关键词： frequency domain,Diffuse optical tomography,image reconstruction
更新于2025-09-04 15:30:14
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Example-based image super-resolution via blur kernel estimation and variational reconstruction
摘要： Single image super-resolution aims at generating clear high-resolution image from one low-resolution image. Due to the limited low-resolution information, it is a challenging task to restore clear, artifacts-free image, meanwhile preserving finer structures and textures. This paper proposes an effective example-based image super-resolution method while making clear image and no compromise on quality. Firstly, the image prior is imposed on the anchor neighborhood regression model to optimize mapping coefficient for interim latent image construction. In order to remove its blur, kernel estimation iteration optimization algorithm is proposed based on the salient edges which are extracted through texture-structure discriminate minimum energy function and fractional order mask enhancement. Finally, an accurate reconstruction constraint combined with a simple gradient regularization is applied to reconstruct the super-resolution image. The proposed method is able to produce clear high-frequency texture details and maintain clean edges even under large scaling factors. Experimental results show that the proposed method performs well in visual effects and similarities. Furthermore, we test our algorithm in multi-texture images for robust evaluation. It is demonstrated that our algorithm is robust under complicated textures condition.
关键词： image reconstruction,super-resolution,fractional-order,blur kernel estimation
更新于2025-09-04 15:30:14
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Confidence interval constraint based regularization framework for PET quantization
摘要： In this paper, a new generic regularized reconstruction framework based on confidence interval constraints for tomographic reconstruction is presented. As opposed to usual state-of-the-art regularization methods that try to minimize a cost function expressed as the sum of a data-fitting term and a regularization term weighted by a scalar parameter, the proposed algorithm is a two-step process. The first step concentrates on finding a set of images that relies on direct estimation of confidence intervals for each reconstructed value. Then, the second step uses confidence intervals as a constraint to choose the most appropriate candidate according to a regularization criterion. Two different constraints are proposed in this paper. The first one has the main advantage of strictly ensuring that the regularized solution will respect the interval-valued data-fitting constraint, thus preventing over-smoothing of the solution while offering interesting properties in terms of spatial and statistical bias/variance trade-off. Another regularization proposition based on the design of a smoother constraint also with appealing properties is proposed as an alternative. The competitiveness of the proposed framework is illustrated in comparison to other regularization schemes using analytical and GATE-based simulation and real PET acquisition.
关键词： confidence intervals,constrained regularization,Image reconstruction,total variation,positron emission tomography
更新于2025-09-04 15:30:14
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[IEEE 2018 37th Chinese Control Conference (CCC) - Wuhan (2018.7.25-2018.7.27)] 2018 37th Chinese Control Conference (CCC) - A Lidar-Based Tree Canopy Detection System Development
摘要： In this paper, a LiDAR-based interactive target detection system was developed to characterized tree canopy structures under various laser sensor travel speed and detection distances. The system composed of a sliding motion control system and a Lidar-based target detection unit. The target detection unit used a 2700 range laser scanning sensor to measure target object surface distances based on the time-of-flight principle. The laser sensor travel speed and travel distance was controlled via the control system by specifying a position and speed as a set point. A real-time data acquisition and data post-processing programs were developed based on C++ and MATLAB programming languages respectively. The entire system was tested in the laboratory for a wide range of parameters and operating conditions. The test result showed that the system could detect and characterize tree canopy structure at very low travel speed (0.3 m/s) and high travel speed (5.0 m/s), respectively with acceptable accuracy.
关键词： Tree canopy,three-dimensional image reconstruction,Precision agriculture,LiDAR,Servo system
更新于2025-09-04 15:30:14