This disclosure provides a method for imaging lymph nodes and lymphatic vessels without a contrast agent. The method includes providing, using an optical source, an infrared illumination to a region of a subject having at least one lymphatic component, detecting a reflected portion of the infrared illumination directly reflected from the region using a sensor positioned thereabout, and generating at least one image indicative of the at least one lymphatic component in the subject using the reflected portion of the infrared illumination.

A medical image segmentation method based on a U-Net, including: sending real segmentation image and original image to a generative adversarial network for data enhancement to generate a composite image with a label; then putting the composite image into original data set to obtain an expanded data set, and sending the expanded data set to improved multi-feature fusion segmentation network for training. A Dilated Convolution Module is added between the shallow and deep feature skip connections of the segmentation network to obtain receptive fields with different sizes, which enhances the fusion of detail information and deep semantics, improves the adaptability to the size of the segmentation target, and improves the medical image segmentation accuracy. The over-fitting problem that occurs when training the segmentation network is alleviated by using the expanded data set of the generative adversarial network.

Video editing software tools platform utilizing a video display to provide access to specific video editing software tools, such as video oriented applications or widgets, that can assist those in a video broadcasting team, such as a camera operator or video editor, with a video broadcast feed. Various video editing software tools can provide features and functions that can add visual context to video data presented in the image stream from the video camera and provide archived information pertaining to the same. Various embodiments relate to systems and methods for simultaneously switching input image streams to output devices, while providing optional image processing functions on the image streams. Certain embodiments may enable multiple users/viewers to collaboratively control such systems and methods.

A method for image analysis of medical test results, comprising receiving, at a server, information from a mobile device regarding test results from a test performed using a testing device, wherein the testing device includes an alignment target disposed on the testing device and a plurality of immunoassay test strips, receiving at the server an image of the testing device from the mobile device, determining by the server RGB values for a plurality of pixels of the image, normalizing by the server the RGB values into a single value, comparing by the server the single value to a control value stored on the server, and providing by the server a risk indicator, wherein the risk indicator indicates a likelihood of a presence of a medical condition.

A method, a system and a computer readable medium for automatic segmentation of a 3D medical image, the 3D medical image comprising an object to be segmented, the method characterized by comprising: carrying out, by using a machine learning model, in at least two of a first, a second and a third orthogonal orientation, 2D segmentations for the object in slices of the 3D medical image to derive 2D segmentation data; determining a location of a bounding box (10) within the 3D medical image based on the 2D segmentation data, the bounding box (10) having predetermined dimensions; and carrying out a 3D segmentation for the object in the part of the 3D medical image corresponding to the bounding box (10).

A method for supporting a user, a corresponding computer program product, a corresponding data medium, and a corresponding imaging system are provided. According to the method, a three-dimensional (3D) data set depicting a target object is provided, and at least one two-dimensional (2D) image of the target object is automatically acquired. The 2D image and the 3D data set are automatically registered with each other by a 2D/3D registration. A spatial direction in which the 2D/3D registration exhibits greatest uncertainty is automatically specified. A signal for aligning an instrument that is provided for the purpose of examining the target object is then automatically generated and output as a function of the specified spatial direction in order to support the user.

Various methods and systems are provided for artifact reduction with resolution preservation. In one example, a method includes obtaining projection data of an imaging subject, identifying a metal-containing region in the projection data, interpolating the metal-containing region to generate interpolated projection data, extracting high frequency content information from the projection data in the metal-containing region, adding the extracted high frequency content information to the interpolated projection data to generate adjusted projection data, and reconstructing one or more diagnostic images from the adjusted projection data.

The present disclosure relates to a method for scanning a patient in an imaging system. The imaging system may include one or more cameras directed at the patient. The method may include obtaining a position of each of the camera(s) relative to the imaging system. The method may also include obtain image data of the patient captured by the camera(s), wherein the image data may correspond to a first view with respect to the patient. The method may further include generating projection image data of the patient based on the image data and the position of each of the camera(s) relative to the imaging system, wherein the projection image data may correspond to a second view with respect to the patient different from the first view. The method may further include generating control information for scanning the patient based on the projection image data of the patient.

The present disclosure is related to systems and methods for orthosis design. The method includes obtaining a three-dimensional (3D) model associated with a subject. The method includes obtaining one or more reference images associated with the subject. The method includes determining, based on the 3D model and the one or more reference images, orthosis design data for the subject. The orthosis design data may be used to determine an orthosis for the subject.

A computer-implemented method is provided for improving live video quality. The method comprises: acquiring, using a medical imaging apparatus, a stream of consecutive image frames of a subject, and the stream of consecutive image frames are acquired with reduced amount of radiation dose; applying a deep learning network model to the stream of consecutive image frames to generate an image frame with improved quality; and displaying the image frame with improved quality in real-time on a display.