分类： 核科学技术 >> 辐射物理与技术 提交时间： 2024-05-30
摘要： Cone-beam computed tomography (CBCT) is mostly used for position verification during the treatment pro#2;cess. However, severe image artifacts in CBCT hinder its direct use in dose calculation and adaptive radiationtherapy re-planning for proton therapy. In this study, an improved U-Net neural network named CBAM-U-Netwas proposed for CBCT noise reduction in proton therapy, which is a CBCT denoised U-Net network with con#2;volutional block attention modules. The datasets contained 20 groups of head and neck images. The CT imageswere registered to CBCT images as ground truth. The original CBCT denoised U-Net network, sCTU-Net, wastrained for model performance comparison. The synthetic CT(SCT) images generated by CBAM-U-Net and theoriginal sCTU-Net are called CBAM-SCT and U-Net-SCT images, respectively. The HU accuracies of the CT,CBCT, and SCT images were compared using four metrics: mean absolute error (MAE), root mean square error(RMSE), peak signal-to-noise ratio (PSNR), and structure similarity index measure (SSIM). The mean values ofthe MAE, RMSE, PSNR, and SSIM of CBAM-SCT images were 23.80 HU, 64.63 HU, 52.27 dB, and 0.9919,respectively, which were superior to those of the U-Net-SCT images. To evaluate dosimetric accuracy, the rangeaccuracy was compared for a single-energy proton beam. The γ-index pass rates of a 4 cm × 4 cm scannedfield and simple plan were calculated to compare the effects of the noise reduction capabilities of the originalU-Net and CBAM-U-Net on the dose calculation results. CBAM-U-Net reduced noise more effectively thansCTU-Net, particularly in high-density tissues. We proposed a CBAM-U-Net model for CBCT noise reductionin proton therapy. Owing to the excellent noise reduction capabilities of CBAM-U-Net, the proposed modelprovided relatively explicit information regarding patient tissues. Moreover, it can be used in dose calculationand adaptive treatment planning in the future.
分类： 物理学 >> 核物理学 提交时间： 2025-03-27
chen, Dr. kai
Xie, Shipeng
Gao, Dr. Yuan
Gu, Dr. Jiabin
Xi, Dr. Yan
Gao, Mrs. Hongyu
Wang, Mr. Zihao
Wu, Dr. Zhan
Tang, Dr. Hui
Chen, Prof. Yang
摘要： Cone-beam computed tomography (CBCT) is widely used for high-precision three-dimensional imaging in the field of nuclear science and technology (e.g., nuclear medicine radiation therapy, nondestructive testing of nuclear facilities). However, when patients with metal implants in their bodies are examined by CT, the projection data will be contaminated and the CT reconstruction will produce severe metal artifacts affecting the diagnostic accuracy. Therefore, developing high-performance metal artifact reduction (MAR) methods for CBCT is essential for clinical diagnosis. Some of the existing MAR methods ignore physical phenomena such as x-ray scattering during CT imaging. The remaining MAR methods utilize scattering correction as a preprocessing approach, and this non-end-to-end MAR method increases the complexity of the MAR process. In this article, we design an end-to-end MAR method that incorporates both scattering correction and metal segmentation in the projection domain in the same network, followed by morphological post-processing and metal artifact suppression. Both qualitative and quantitative results and analyses in simulated and real data sets illustrate the superiority of this end-to-end MAR method.
分类： 核科学技术 >> 核探测技术与核电子学 提交时间： 2023-06-18 合作期刊: 《Nuclear Science and Techniques》
摘要： In helical cone-beam computed tomography (CT), Feldkamp-Davis-Kress (FDK) based image reconstruction algorithms are by far the most popular. However, artifacts are commonly met in the presence of lateral projection truncation. The reason is that the ramp filter is global. To restrain the truncation artifacts, an approximate reconstruction formula is proposed based on the Derivative-Hilbert-Backprojection (DHB) framework. In the method, the first order derivative filter is followed by the Hilbert transform. Since the filtered projection values are almost zero by the first order derivative filter, the following Hilbert transform has little influence on the projection values, even though the projections are laterally truncated. The proposed method has two main advantages. First, it has comparable computational efficiency and image quality as well as the conventional helical FDK algorithm for non-truncated projections. The second advantage is that images can be reconstructed with acceptable quality and much lower computational cost in comparison to the Laplace operator based algorithm in cases with truncated projections. To point out the advantages of our method, simulations on the computer and real data experiments on our laboratory industrial cone-beam CT are conducted. The simulated and experimental results demonstrate that the method is feasible for image reconstruction in the case of projection truncation.
分类： 物理学 >> 核物理学 提交时间： 2025-04-17
chen, Dr. kai
Xie, Shipeng
Gao, Mrs. Hongyu
Gao, Dr. Yuan
Xi, Dr. Yan
Li, Mr. Yuchen
Chen, Prof. Yang
摘要： CT images provide medical practitioners with a scientific and intuitive rationale for the diagnosis of clinical diseases. The Internet of Medical Things (IoMT) and telemedicine facilitate the preservation, transmission, and application of medical data, driving the sharing of medical data, especially medical images. Encryption and decryption of CT images distributed in the IoMT and telemedicine are becoming critical because they contain a large amount of private patient-sensitive information and are vulnerable to third-party attacks, resulting in information exposure and privacy leakage . In this paper, we propose an Encryption and Decryption based Gan-attention network (EDG-Net) for CT images in the IoMT and telemedicine. EDG-Net consists of a generator, two discriminators, a domain transfer of attention, and adaptive normalization. In addition, a double encryption and decryption strategy is introduced by EDG-Net to effectively improve the security of the ciphertext image and the fidelity of the decrypted plaintext image. Specifically, during the encryption or decryption phase, the generator transforms the CT images mutually in the plaintext and ciphertext domains. Two discriminators to identify and modify the differences between these two domain transformations, especially to improve the accuracy of the reconstruction during decryption. The parameters of the trained encryption and decryption network are considered as the secret keys of encryption and decryption. Qualitative and quantitative analysis of public and private datasets demonstrates the superior performance of EDG-Net regarding encryption security and robustness, as well as decryption accuracy.
分类： 核科学技术 >> 粒子加速器 提交时间： 2023-06-18 合作期刊: 《Nuclear Science and Techniques》
摘要： CBCT scanners have been widely used in angiography, radiotherapy guidance, mammography and oral maxillofacial imaging. To cut detector size, reduce manufacturing costs and radiation dose while keeping a reasonable FOV, the flat panel detector can be placed off-center horizontally. This scanning configuration extends the FOV effectively. However, each projection is transversely truncated, bringing errors and artifacts in reconstruction. In this paper, a simple but practical method is proposed for this scanning geometry based on truncation compensation and the modified FDK algorithm. Numerical simulations with jaw phantom were conducted to evaluate the accuracy and practicability of the proposed method. A novel CBCT system for maxillofacial imaging is used for clinical test, which is equipped with an off-center small size flat panel detector. Results show that reconstruction accuracy is acceptable for clinical use, and the image quality appears sufficient for specific diagnostic requirements. It provides a novel solution for clinical CBCT system, in order to reduce radiation dose and manufacturing cost.
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