To address the problem that the imaging inversion method based on a single model in integrated aperture imaging is difficult to effectively correct model errors and perform accurate image reconstruction, a dual-model (DM)-based integrated aperture imaging inversion method is proposed for correcting the parametric errors of the inversion model and performing highly accurate millimeter-wave image reconstruction of the target scene. In view of the different parameter sensitivities of the Fourier transform (MFFT) model and the G-matrix (GM) model, the proposed DM method first corrects the imaging parameters with errors accurately by comparing the reconstruction errors of the two models; then recon-structs a high-precision target image based on the accurate GM model with the help of an improved regularization method. It is proved by simulation experiments that the proposed DM method can effectively correct the parameter errors of the imaging model and reconstruct the target scene with high accuracy in millimeter wave images compared with the traditional single-model imaging method.
Using a Global Trade Analysis Project (GTAP) model, and China as the base for analytical comparison, this paper shows that there are significant economic benefits to China and the participating countries along all six Belt and Road Initiative (BRI) economic corridors. However, to maximize these benefits, the social and environmental risks need to be well managed. The analysis shows a clear sequencing in terms of priority corridors. Two corridors have minimal investments and immediate returns, two corridors have significant investments with huge returns, and two corridors have high investments with lower returns. Overall, the paper demonstrates that to ensure the sustainability of any BRI corridor development, there is a need to consider its costs and benefits from the economic, social and environmental perspectives.
In the process of X-ray transmission imaging, the mutual occlusion between structures will lead to the image information overlap, and the computed tomography (CT) method is often required to obtain the structure information at different depths, but with low efficiency. To address these problems, an X-ray focused on imaging algorithm based on multi-line scanning is proposed, which only requires the scene target to pass through the detection area along a straight line to extract multi-view information, and uses the optical field reconstruction theory to achieve the de-obscured reconstruction of the structure at a specified depth with high real-time. The results of multi-line scan and X-ray reconstruction of the target show that the proposed method can reconstruct the information of any specified depth layer, and it can perform fast imaging detection of the mutually occluded target structures and improve the recognition of the occluded targets, which has a good application prospect.
The Agriculture Trading Platform (ATP) represents a significant innovation in the realm of agricultural trade in Malaysia. This web-based platform is designed to address the prevalent inefficiencies and lack of transparency in the current agricultural trading environment. By centralizing real-time data on agricultural production, consumption, and pricing, ATP provides a comprehensive dashboard that facilitates data-driven decision-making for all stakeholders in the agricultural supply chain. The platform employs advanced deep learning algorithms, including Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN), to forecast market trends and consumption patterns. These predictive capabilities enable producers to optimize their market strategies, negotiate better prices, and access broader markets, thereby enhancing the overall efficiency and transparency of agricultural trading in Malaysia. The ATP’s user-friendly interface and robust analytical tools have the potential to revolutionize the agricultural sector by empowering farmers, reducing reliance on intermediaries, and fostering a more equitable trading environment.
Multiple myeloma (MM) is a hematologic cancer characterized by clonal proliferation of plasma cells within the bone marrow. It is the most serious form of plasma cell dyscrasias, whose complications—hypercalcemia, renal failure, anemia, and lytic bone lesions—are severe and justify the therapeutic management. Imaging of bone lesions is a cardinal element in the diagnosis, staging, study of response to therapy, and prognostic evaluation of patients with MM. Historically, the skeletal radiographic workup (SRW), covering the entire axial skeleton, has been used to detect bone lesions. Over time, new imaging techniques that are more powerful than SRW have been evaluated. Low-dose and whole-body computed tomography (CT) supplants SRW for the detection of bone involvement, but is of limited value in assessing therapeutic response. Bone marrow MRI, initially studying the axial pelvic-spinal skeleton and more recently the whole body, is an attractive alternative. Beyond its non-irradiating character, its sensitivity for the detection of marrow damage, its capacity to evaluate the therapeutic response and its prognostic value has been demonstrated. This well-established technique has been incorporated into disease staging systems by many health systems and scientific authorities. Along with positron emission tomography (PET)-18 fluorodeoxyglucose CT, it constitutes the current imaging of choice for MM. This article illustrates the progress of the MRI technique over the past three decades and situates its role in the management of patients with MM.
The present work shows an application of the Chan-Vese algorithm for the semi-automatic segmentation of anatomical structures of interest (lungs and lung tumor) in 4DCT images of the thorax, as well as their three-dimensional reconstruction. The segmentation and reconstruction were performed on 10 CT images, which make up an inspiration-expiration cycle. The maximum displacement was calculated for the case of the lung tumor using the reconstructions of the onset of inspiration, the onset of expiration, and the voxel information. The proposed method achieves appropriate segmentation of the studied structures regardless of their size and shape. The three-dimensional reconstruction allows us to visualize the dynamics of the structures of interest throughout the respiratory cycle. In the future, it is expected to have more evidence of the good performance of the proposed method and to have the feedback of the clinical expert, since the knowledge of the characteristics of anatomical structures, such as their dimension and spatial position, helps in the planning of Radiotherapy (RT) treatments, optimizing the radiation dose to cancer cells and minimizing it in healthy organs. Therefore, the information found in this work may be of interest for the planning of RT treatments.
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