Objective: to determine the diagnostic performance of magnetic resonance hysterosalpingography (HSG-MRI), using laparoscopy as the reference method. Materials and methods: 22 patients were included. All underwent HSG-MRI with a 1.5 Tesla resonator and then laparoscopy with chromotubation. Two radiologists examined the MRIs, determining tubal patency by consensus. Descriptive and diagnostic performance analyses were performed. Results: HSG-MRI had a success rate of 91%. Study duration was 49 ± 15 minutes, volume injected 26 ± 16 cm³ and pain scale 30 ± 19 out of 100. Sensitivity and specificity of HSG-MRI were 100% for global and left Cotte test, and 25% and 93.3% for right Cotte test, respectively. There were 2 minor complications and no major complications. Discussion: our initial results demonstrated high sensitivity and specificity. Although other studies analyzed the ability of HSG-MRI to assess tubal patency with good results, the use of a flawed reference standard left room for reasonable doubt, preventing a recommendation based on solid evidence. However, when comparing our results with those published, we observed a high degree of concordance insofar as the positive effusion is correctly diagnosed with a specificity of 100% or with a percentage close to this figure.

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.

With the increasing demand for sustainable energy, advanced characterization methods are becoming more and more important in the field of energy materials research. With the help of X-ray imaging technology, we can obtain the morphology, structure and stress change information of energy materials in real time from two-dimensional and three-dimensional perspectives. In addition, with the help of high penetration X-ray and high brightness synchrotron radiation source, in-situ experiments are designed to obtain the qualitative and quantitative change information of samples during the charge and discharge process. In this paper, X-ray imaging technology based on synchrotron and its related applications are reviewed. The applications of several main X-ray imaging technologies in the field of energy materials, including X-ray projection imaging, transmission X-ray microscopy, scanning transmission X-ray microscopy, X-ray fluorescence microscopy and coherent diffraction imaging, are discussed. The application prospects and development directions of X-ray imaging in the future are prospected.

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.

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.