- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Low-Dose Computed Tomography Image Super-Resolution Reconstruction via Random Forests
摘要： Aiming at reducing computed tomography (CT) scan radiation while ensuring CT image quality, a new low-dose CT super-resolution reconstruction method based on combining a random forest with coupled dictionary learning is proposed. The random forest classifier finds the optimal solution of the mapping relationship between low-dose CT (LDCT) images and high-dose CT (HDCT) images and then completes CT image reconstruction by coupled dictionary learning. An iterative method is developed to improve robustness, the important coefficients for the tree structure are discussed and the optimal solutions are reported. The proposed method is further compared with a traditional interpolation method. The results show that the proposed algorithm can obtain a higher peak signal-to-noise ratio (PSNR) and structural similarity index measurement (SSIM) and has better ability to reduce noise and artifacts. This method can be applied to many different medical imaging fields in the future and the addition of computer multithreaded computing can reduce time consumption.
关键词： super-resolution,coupled dictionary learning,random forests,low-dose CT
更新于2025-09-23 15:22:29
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Facile preparation of new polystyrene leucomalachite green thick films and study of their radiochromic behavior for low doses of gamma radiation
摘要： Colourless polystyrene-leucomalachite green (PS-LMG) thick films containing a suitable chloroalkane were prepared by a fast and facile casting method, and were investigated for their radio chromic response behavior under the influence of 1.25 MeV γ-radiation. Their gamma response was studied in the 0.05 kGy to 10 kGy range to evaluate their suitability for potential use as the dosimeter in the radiation processing industries. The films were found to undergo a visibly distinct green coloration in the studied range, with the colour intensity increasing with an increase in the total dose. The radiochromic response of these films when investigated as a function of film thickness showed that the colour development as well as the linearity of the response was markedly affected by the thickness of the films. The effect of dye loading and the chloroalkane concentration on the radiochromic response of these films were also investigated. Depending upon the film thickness and reactant concentrations, the films were found to be capable of visually detecting gamma radiation doses as low as few tens of grays.
关键词： Polystyrene,Thick Films,Leucomalachite Green,Radiochromic,Low Dose
更新于2025-09-23 15:22:29
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Novel SPECT Technologies and Approaches in Cardiac Imaging
摘要： Recent novel approaches in myocardial perfusion single photon emission CT (SPECT) have been facilitated by new dedicated high-efficiency hardware with solid-state detectors and optimized collimators. New protocols include very low-dose (1 mSv) stress-only, two-position imaging to mitigate attenuation artifacts, and simultaneous dual-isotope imaging. Attenuation correction can be performed by specialized low-dose systems or by previously obtained CT coronary calcium scans. Hybrid protocols using CT angiography have been proposed. Image quality improvements have been demonstrated by novel reconstructions and motion correction. Fast SPECT acquisition facilitates dynamic flow and early function measurements. Image processing algorithms have become automated with virtually unsupervised extraction of quantitative imaging variables. This automation facilitates integration with clinical variables derived by machine learning to predict patient outcome or diagnosis. In this review, we describe new imaging protocols made possible by the new hardware developments. We also discuss several novel software approaches for the quantification and interpretation of myocardial perfusion SPECT scans.
关键词： fast myocardial perfusion single photon emission computed tomography,quantification,single photon emission computed tomography,low dose,myocardial perfusion imaging,stress only
更新于2025-09-23 15:22:29
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Modulation Properties of an Extended Cavity Diode Laser and Dynamic Mode Splitting
摘要： Low-dose CT (LDCT) images tend to be degraded by excessive mottle noise and steak artifacts. In this paper, we proposed a novel fractional-order differentiation model that can be applied to LDCT image processing as a post-processing technique. The anisotropic diffusion model (proposed by Perona and Malik, i.e., PM model) has good performance in flat regions, total variation (TV) model works better in edge preservation, and fractional-order differentiation models can mitigate block effect while preserving fine details and more structure. The proposed model is based on the weighted combinations of the fractional-order PM model and the fractional-order TV model, which maintains the advantages of PM model, TV model, and fractional-order differentiation models. Moreover, the local intensity variance was added to both weighted coefficient and diffusion coefficient of the proposed model to properly preserve edges and details. A variety of simulated phantom data, including the Shepp–Logan head phantom, the pelvis phantom, and the actual thoracic phantom, were used for experimental validation. The results of numerical simulation and clinical data experiments demonstrate that the proposed approach has a better performance in both noise suppression and detail preservation, when compared with several other existing methods.
关键词： edge and detail preservation,fractional-order differentiation model,Low-dose CT,image processing
更新于2025-09-23 15:21:01
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Statistical CT reconstruction using region-aware texture preserving regularization learning from prior normal-dose CT image
摘要： In some clinical applications, prior normal-dose CT (NdCT) images are available, and the valuable textures and structure features in them may be used to promote follow-up low-dose CT (LdCT) reconstruction. This study aims to learn texture information from the NdCT images and leverage it for follow-up LdCT image reconstruction to preserve textures and structure features. Specifically, the proposed reconstruction method first learns the texture information from those patches with similar structures in NdCT image, and the similar patches can be clustered by searching context features efficiently from the surroundings of the current patch. Then it utilizes redundant texture information from the similar patches as a priori knowledge to describe specific regions in the LdCT image. The advanced region-aware texture preserving prior is termed as ‘RATP’. The main advantage of the PATP prior is that it can properly learn the texture features from available NdCT images and adaptively characterize the region-specific structures in the LdCT image. The experiments using patient data were performed to evaluate the performance of the proposed method. The proposed RATP method demonstrated superior performance in LdCT imaging compared to the filtered back projection (FBP) and statistical iterative reconstruction (SIR) methods using Gaussian regularization, Huber regularization and the original texture preserving regularization.
关键词： texture preserving,statistical iterative reconstruction,low-dose,a priori image,CT imaging
更新于2025-09-23 15:21:01
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[IEEE 2019 19th International Workshop on Junction Technology (IWJT) - Kyoto, Japan (2019.6.6-2019.6.7)] 2019 19th International Workshop on Junction Technology (IWJT) - Aspects of Highly-channeled MeV Implants of Dopants in Si(100)
摘要： Low-dose CT (LDCT) images tend to be degraded by excessive mottle noise and steak artifacts. In this paper, we proposed a novel fractional-order differentiation model that can be applied to LDCT image processing as a post-processing technique. The anisotropic diffusion model (proposed by Perona and Malik, i.e., PM model) has good performance in flat regions, total variation (TV) model works better in edge preservation, and fractional-order differentiation models can mitigate block effect while preserving fine details and more structure. The proposed model is based on the weighted combinations of the fractional-order PM model and the fractional-order TV model, which maintains the advantages of PM model, TV model, and fractional-order differentiation models. Moreover, the local intensity variance was added to both weighted coefficient and diffusion coefficient of the proposed model to properly preserve edges and details. A variety of simulated phantom data, including the Shepp–Logan head phantom, the pelvis phantom, and the actual thoracic phantom, were used for experimental validation. The results of numerical simulation and clinical data experiments demonstrate that the proposed approach has a better performance in both noise suppression and detail preservation, when compared with several other existing methods.
关键词： image processing,edge and detail preservation,fractional-order differentiation model,Low-dose CT
更新于2025-09-23 15:19:57
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Pipeline Leak Detection Technology Based on Distributed Optical Fiber Acoustic Sensing System
摘要： Low-dose CT (LDCT) images tend to be degraded by excessive mottle noise and steak artifacts. In this paper, we proposed a novel fractional-order differentiation model that can be applied to LDCT image processing as a post-processing technique. The anisotropic diffusion model (proposed by Perona and Malik, i.e., PM model) has good performance in flat regions, total variation (TV) model works better in edge preservation, and fractional-order differentiation models can mitigate block effect while preserving fine details and more structure. The proposed model is based on the weighted combinations of the fractional-order PM model and the fractional-order TV model, which maintains the advantages of PM model, TV model, and fractional-order differentiation models. Moreover, the local intensity variance was added to both weighted coefficient and diffusion coefficient of the proposed model to properly preserve edges and details. A variety of simulated phantom data, including the Shepp–Logan head phantom, the pelvis phantom, and the actual thoracic phantom, were used for experimental validation. The results of numerical simulation and clinical data experiments demonstrate that the proposed approach has a better performance in both noise suppression and detail preservation, when compared with several other existing methods.
关键词： image processing,edge and detail preservation,fractional-order differentiation model,Low-dose CT
更新于2025-09-23 15:19:57
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Quantitative analyses of amount and localization of radiosensitizer gold nanoparticles interacting with cancer cells to optimize radiation therapy
摘要： Previous studies showed that gold nanoparticles (AuNPs) are useful radiosensitizers which optimize radiation therapy under low-dose radiation. However, the mechanisms of AuNP radiosensitization, including the amount and localization of the AuNPs interacting with cancer cells, has not yet been quantified. To answer these questions, we prepared AuNPs conjugated with anti-human epidermal growth factor receptor type 2 (HER2) antibody via polyethylene glycol (PEG) chains (AuNP-PEG-HER2ab). AuNP-PEG-HER2ab specifically bound to the HER2-expressing cancer cells and entered the cells via endocytosis. Whether endocytosis of AuNP-PEG-HER2ab occurred had no effect on radiosensitization efficacy by AuNP-PEG-HER2ab in vitro. The radiosensitization efficacy in vitro depended on dose of AuNP-PEG-HER2ab or dose of X-ray. Moreover, AuNP-PEG-HER2ab administrated into tumor-bearing mice was localized to both the periphery of the tumor tissue and near the nuclei in cancer cells in tumor deep tissue. The localization of AuNP-PEG-HER2ab in tumor tissues was important factors for in vivo powerful radiosensitization efficacy.
关键词： Radiation therapy,Radiosensitizer,Low-dose radiation,Gold nanoparticle,HER2
更新于2025-09-23 15:19:57
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Low-dose single-energy material decomposition in radiography using a sparse-view computed tomography scan
摘要： Dual-energy material decomposition (DEMD) is a well-established theoretical x-ray technique that uses low- and high-kilovoltage radiographs to separate soft tissue and bone in radiography and computed tomography (CT). However, it requires double exposures that result in increased patient radiation doses, causes increases in the execution time, and generates errors due to misregistration attributed to the patient motion between two scans. In this study, we investigated a low-dose, single-energy material decomposition (LSEMD) method in radiography using a sparse-view computed tomography scan where the attenuation length in the object was estimated from the CT image. We performed a systematic simulation and an experiment to demonstrate the feasibility of use of the LSEMD method in radiography. Only 60 projections, far fewer than those required by the Nyquist sampling theory, were acquired at an x-ray tube voltage of 80 kVp, and were used to reconstruct a sparse-view CT image with a state-of-the-art dictionary-learning (DL) algorithm. We investigated the image performance of the LSEMD and compared the elicited results with those obtained with the use of DEMD (80 kVp and 120 kVp were used). Our results indicate that the DL algorithm produced high-quality sparse-view CT images. Accordingly, the LSEMD method yielded material decomposition results that were very similar to the results elicited by the conventional DEMD method in radiography.
关键词： dictionary-learning,low-dose single-energy material decomposition,Computed tomography,dual-energy material decomposition
更新于2025-09-19 17:15:36
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[IEEE 2019 European Space Power Conference (ESPC) - Juan-les-Pins, France (2019.9.30-2019.10.4)] 2019 European Space Power Conference (ESPC) - III-V on Si solar cells behavior at NIRT and LILT conditions for space applications
摘要： Low-dose CT (LDCT) images tend to be degraded by excessive mottle noise and steak artifacts. In this paper, we proposed a novel fractional-order differentiation model that can be applied to LDCT image processing as a post-processing technique. The anisotropic diffusion model (proposed by Perona and Malik, i.e., PM model) has good performance in ?at regions, total variation (TV) model works better in edge preservation, and fractional-order differentiation models can mitigate block effect while preserving ?ne details and more structure. The proposed model is based on the weighted combinations of the fractional-order PM model and the fractional-order TV model, which maintains the advantages of PM model, TV model, and fractional-order differentiation models. Moreover, the local intensity variance was added to both weighted coef?cient and diffusion coef?cient of the proposed model to properly preserve edges and details. A variety of simulated phantom data, including the Shepp–Logan head phantom, the pelvis phantom, and the actual thoracic phantom, were used for experimental validation. The results of numerical simulation and clinical data experiments demonstrate that the proposed approach has a better performance in both noise suppression and detail preservation, when compared with several other existing methods.
关键词： edge and detail preservation,fractional-order differentiation model,Low-dose CT,image processing
更新于2025-09-19 17:13:59