Abstract: Embodiments of this application disclose an image processing method performed by a computer device, and a computer-readable storage medium.

Abstract: A medical image processing method is provided to a data processing device. The method includes obtaining a medical image, obtaining a feature map and a medical image content recognition result that correspond to the medical image by using a medical image classification model, or obtaining the feature map and a lesion classification result that correspond to the medical image by using the medical classification model, the feature map including N channels, N being an integer greater than 1, generating a thermodynamic diagram corresponding to the medical image content recognition result or the lesion classification result according to the feature map and a weight parameter set, the weight parameter set including N weight parameters, the weight parameters having a correspondence with the channels, and generating an image recognition result corresponding to the medical image according to the thermodynamic diagram.

Abstract: A medical endoscope image recognition method is provided. In the method, endoscope images are received from a medical endoscope. The endoscope images are filtered with a neural network, to obtain target endoscope images. Organ information corresponding to the target endoscope images is recognized via the neural network. An imaging type of the target endoscope images is identified according to the corresponding organ information with a classification network. A lesion region in the target endoscope images is localized according to an organ part indicated by the organ information. A lesion category of the lesion region in an image capture mode of the medical endoscope corresponding to the imaging type is identified.

Abstract: This application relates to an image recognition model training method, an image recognition method, apparatus, and system. The method includes: obtaining a to-be-recognized image; extracting image feature information of the to-be-recognized image; and obtaining a lesion category recognition result of the to-be-recognized image by using the image feature information of the to-be-recognized image as an input parameter of a preset image recognition model, the image recognition model being trained by using a training image sample set comprising at least one strong-label training image sample, to determine the lesion category recognition result; and the strong-label training image sample representing an image sample having strong-label information, and the strong-label information comprising at least annotation information of a lesion category and a lesion position in the strong-label training image sample.

Abstract: The present disclosure relates to composition and methodology for using the CD2 receptor to block viral replication, such as HIV-1 infection. In one embodiment, viral target cells such as blood CD4 T cells can be rendered resistant to HIV through stimulation of the CD2 receptor with either an antibody, a ligand, or a small molecule that binds to the CD2 receptor. Pre-stimulation of CD2 can be used to enhance the anti-HIV immunity and used to promote immune response from HIV infection or from an anti-HIV vaccine.

Abstract: Embodiments of this application include an image processing method and apparatus, a non-transitory computer-readable storage medium, and an electronic device. In the image processing method a to-be-predicted medical image is input into a multi-task deep convolutional neural network model. The multi-task deep convolutional neural network model includes an image input layer, a shared layer, and n parallel task output layers. One or more lesion property prediction results of the to-be-predicted medical image is output through one or more of the n task output layers. The multi-task deep convolutional neural network model is trained with n types of medical image training sets, n being a positive integer that is greater than or equal to 2.

Abstract: The present disclosure describes a method, an apparatus, and storage medium for recognizing medical image. The method includes obtaining, by a device, a medical image. The device includes a memory storing instructions and a processor in communication with the memory. The method further includes determining, by the device, the medical image through a first recognition model to generate a lesion recognition result used for indicating whether the medical image comprises a lesion; and in response to the lesion recognition result indicating that the medical image comprises a lesion, recognizing, by the device, the medical image through a second recognition model to generate a lesion degree recognition result of the medical image used for indicating a degree of the lesion. Manual analysis and customization of a feature extraction solution are not required, so that the efficiency and accuracy of medical image recognition are improved.

Abstract: A major immune dysfunction persisting in chronic diseases such as HIV infection and cancer is the impairment of T cell motility and migration to tissues. Therapeutics such as antiretroviral therapy or cancer therapy frequently do not fully restore T cell motility for tissue migration and infiltration. Cofilin is an actin-depolymerizing factor that regulates actin dynamics for T cell migration. Here we demonstrate that the levels of cofilin phosphorylation in blood T cells (CD4 or CD8), macrophages, B cells, natural killer (NK) cells, and/or cancer cells can be used to quantify the immune damages caused by chronic viral infection and cancer, and to predict the recovery of T cells following treatment.

Abstract: A colon polyp image processing method and apparatus and a system are disclosed in the embodiments of this application to detect a position of a polyp in real time and determine a property of the polyp, and thereby improve the processing efficiency of a polyp image. Embodiment of this application provide a colon polyp image processing method that can include detecting a position of a polyp in a to-be-processed endoscopic image by using a polyp positioning model, and positioning a polyp image block in the endoscopic image. The polyp image block can include a position region of the polyp in the endoscopic image. The method can further include performing a polyp type classification type on the polyp image block by using a polyp property identification model, and outputting an identification result.

Abstract: A bed board for a diagnostic bed of a medical examination apparatus is formed in a material that includes basalt fibers. The bed board may have a bed board body composed of basalt fibers and a filler in a predetermined ratio, or may be formed by a hollow shell, composed of basalt fibers and a binder in a predetermined ratio, with the hollow shell being filled by a filler material.

Abstract: A bed board for a diagnostic bed of a medical examination apparatus is formed in a material that includes basalt fibers. The bed board may have a bed board body composed of basalt fibers and a filler in a predetermined ratio, or may be formed by a hollow shell, composed of basalt fibers and a binder in a predetermined ratio, with the hollow shell being filled by a filler material.

Abstract: Systems and methods are provided for updating one or more scanning rules. For example, one or more first operation records being uploaded are obtained; scanning information corresponding to the first operation records is extracted; one or more recommended operations corresponding to the scanning information are obtained based on at least information associated with one or more scanning rules; a matching degree between the first operation records and the recommended operations is calculated; and the scanning rules are updated based on information associated with the matching degree.

Abstract: A device for driving the lifting movement of an examination bed includes a horizontal support frame and a base support component that is pivotally connected to a swing arm component. The device includes a swing bar component including a swing bar. A first end of the swing bar is connected to a lifting movement element, and a second end of the swing bar is connected to a set position of the swing arm component. The device includes a sliding component including a linear guide element and at least one sliding element slidable relative to the linear guide element. The device also includes a swing arm component including at least one swing arm, with the first end of each of the swing arms being connected to the base support component and the second end of each of the swing arms being connected to the sliding element.

Abstract: A system repair method and device, and a storage medium are provided. The system repair method includes: performing security check on system files and registries in a system; when the detection result is abnormal, judging whether the system files and/or the g registries are required to be repaired according to preset system repair rules; and if yes, repairing the system files and/or the registries. The present invention avoids possible abnormal repair in system repair, reduces risks in the system repair, improves security and accuracy of the system repair, and ensures reliability of the system repair.

Abstract: Systems and methods are provided for updating one or more scanning rules. For example, one or more first operation records being uploaded are obtained; scanning information corresponding to the first operation records is extracted; one or more recommended operations corresponding to the scanning information are obtained based on at least information associated with one or more scanning rules; a matching degree between the first operation records and the recommended operations is calculated; and the scanning rules are updated based on information associated with the matching degree.

Abstract: A device for driving the lifting movement of an examination bed includes a horizontal support frame and a base support component that is pivotally connected to a swing arm component. The device includes a swing bar component including a swing bar. A first end of the swing bar is connected to a lifting movement element, and a second end of the swing bar is connected to a set position of the swing arm component. The device includes a sliding component including a linear guide element and at least one sliding element slidable relative to the linear guide element. The device also includes a swing arm component including at least one swing arm, with the first end of each of the swing arms being connected to the base support component and the second end of each of the swing arms being connected to the sliding element.

Abstract: The present embodiments provide a movable examination bed that includes a movable platform for supporting an object to be examined, a supporting body connected to the movable platform from below and used for supporting the movable platform, and a guide rail arranged underneath the movable platform. The examination bed also includes a transport mechanism that drives the supporting body such that the supporting body moves on the guide rail. The examination bed includes a connection mechanism securely connected to the transport mechanism, an electromagnet fixed to the connection mechanism and operable to magnetically attract the supporting body, and a controller operable to control the magnetic attraction between the electromagnet and the supporting body. The examination bed is operable to rapidly separate the movable platform from the transport mechanism in case of an emergency and return the movable platform to an original position after the emergency situation is over.

Abstract: A gap protection device for an examining table includes a guide rail, a protecting chain and a rigid rope. The guide rail is fixed onto the non-moving part of the examining table. One end of the protecting chain is fixed onto the body of the examining table and is movable along the guide rail so as to cover the gap between the body and the non-moving part of the examining table. The two ends of the rigid rope are respectively connected to the two ends of the protecting chain. When the examining table is moved, the closed loop formed by the protecting chain and the rigid rope circulates synchronously under the drive of the examining table, such that the protecting chain covers the gap between the body and the non-moving part of the examining table.