Non-rigid registration plays an important role in medical image analysis. U-Net has been proven to be a hot research topic in medical image analysis and is widely used in medical image registration. However, existing registration models based on U-Net and its variants lack sufficient learning ability when dealing with complex deformations, and do not fully utilize multi-scale contextual information, resulting insufficient registration accuracy. To address this issue, a non-rigid registration algorithm for X-ray images based on deformable convolution and multi-scale feature focusing module was proposed. First, it used residual deformable convolution to replace the standard convolution of the original U-Net to enhance the expression ability of registration network for image geometric deformations. Then, stride convolution was used to replace the pooling operation of the downsampling operation to alleviate feature loss caused by continuous pooling. In addition, a multi-scale feature focusing module was introduced to the bridging layer in the encoding and decoding structure to improve the network model’s ability of integrating global contextual information. Theoretical analysis and experimental results both showed that the proposed registration algorithm could focus on multi-scale contextual information, handle medical images with complex deformations, and improve the registration accuracy. It is suitable for non-rigid registration of chest X-ray images.
With the widespread adoption of antiretroviral therapy, vast improvements in the life expectancy of individuals infected with human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) were seen, and the liver disease of this population has become a leading cause of mortality. Although liver transplantation is as an effective treatment for end-stage liver disease, it remains in its nascent stage for the patients with HIV/AIDS in China, lacking standardized protocols and substantial clinical experience. Therefore, a “Multicenter expert consensus on perioperative management of liver transplantation in patients with human immunodeficiency virus infection” was formulated. This expert consensus aims to standardize and optimize the diagnosis and treatment process for liver transplantation in HIV-infected patients, providing systematic guidance for this procedure in China and fostering multidisciplinary collaboration and development in the field. This expert consensus clearly delineates the indications and contraindications for liver transplantation in HIV-infected patients, emphasizing comprehensive preoperative evaluations of both donors and recipients. These evaluations include infection control measures, immune function monitoring, and management of comorbidities. In terms of surgical procedures, strategies to prevent occupational exposure and intraoperative guidelines are outlined. Postoperatively, the focus is on antiviral therapy, individualized immunosuppression management, and vigilant monitoring of complications to ensure patient recovery and long-term survival. The long-term follow-up management prioritizes regular assessments of liver function, immune status, and HIV-related indicators to adjust treatment plans and enhance patient survival rates and quality of life. With the continuous enrichment of clinical experience and the progress of clinical research, this consensus will be continuously updated.