A method for facilitating a Parkinson's Disease (“PD”) assessment of a patient includes capturing first video of a patient performing first test movements while holding the mobile device; capturing second video of the patient performing second test movements while maintaining the mobile device on their person; capturing third video of the patient performing third test movements including standing and walking; capturing one or more IMU readings using an IMU of the mobile device; processing the first video, the second video, and the third video according to (i) a hand landmark model to generate one or more hand biomarkers, (ii) a face landmark model to generate one or more face biomarkers, and (iii) a body landmark model to generate one or more body biomarkers; and determining an assessment score based on a standardized PD assessment by processing the biomarkers.

Systems and methods are provided for automated identification of vascular pathology in computed tomography images. A region of interest in a chest of a patient is imaged via a computed tomography scanner to provide an image. The region of interest includes at least one of the ascending aorta, the central pulmonary artery, the left and right pulmonary arteries, the lobar arteries extending from the left and right pulmonary arteries, the aortic arch, and the descending aorta of the patient. For each of a plurality of locations within the region of interest, a value representing a variation in radiodensity values for voxels within the location is determined from the image to provide a set of variation values. At a derived model, a parameter representing vascular pathology within the patient is determined from the set of variation values and provided to a user at an associated output device.

The present disclosure provides a method and system for a dynamic fluoroscopy of a C-shaped arm device. The method comprises: photographing a subject during a photography cycle, obtaining, during the photography cycle, first fluoroscopic data of a radiation source irradiating the subject at a first energy, and obtaining second fluoroscopic data of the radiation source irradiating the subject at a second energy different from the first energy (210); photographing the subject in multiple successive photography cycles (220); and displaying a dynamic image of the subject based on the first fluoroscopic data and the second fluoroscopic data obtained in each of the multiple successive photography cycles (230).

The present disclosure provides a system and method for magnetic resonance imaging. The method may include obtaining reference information associated with at least two regions of interest (ROIs) of a subject. The method may also include obtaining a plurality of images associated with the at least two ROIs, the plurality of images being determined based on scanning data of the at least two ROIs generated in a single scan performed on the at least two ROIs by an imaging device. The method may further include identifying local images of each of the at least two ROIs from the plurality of images based on the reference information.

An ultrasound imaging system includes a cine buffer in which image frames produced during an examination are stored. A processor is programmed to select one or more image frames from the cine buffer for presentation to an operator for approval and inclusion in a patient record or other report. The operator can accept the proposed image frames or can select one or more other image frames from the cine buffer. The processor may select image frames at spaced intervals in the cine buffer for presentation. Alternatively, the processor compares image frames in the cine buffer with one or more target image frames. Image frames that are similar to the target image frames are presented to the operator to confirm. Alternatively, image frames can be selected by the processor that contain a specific feature or that are similar to image frames that were previously selected by the operator when performing a particular type of examination.

A method (900) of generating an atlas for a universal atlas database (901) is provided. A new medical scan image (905) is provided. A universal auto-contouring operation (920) is performed on the medical scan image, to generate a set of universal contours (930) for the medical scan image. A local auto-contouring customisation operation (940) is performed on the medical scan image, to generate a set of local contours (950) for the medical scan image. The set of local contours is standardised (980) using a trained model to compensate for biases in the set of local contours, thereby creating a set of standardised global contours (985) for the medical scan image. The set of standardised global contours (985) and the medical scan image (905) can be added to the universal atlas database (901) as a new atlas, thereby expanding the set of atlases that are available in the universal atlas database.

A controller for preparing an image for segmenting includes a memory that stores instructions, and a processor that executes the instructions. When executed by the processor, the instructions cause the controller to perform a process that includes displaying a first modeled tissue structure of a first type, and displaying an image of a first tissue structure of the first type separate from the first modeled tissue structure. The process also includes identifying, on the first modeled tissue structure, landmarks on the first modeled tissue structure for identification on the image of the first tissue structure, and sequentially accentuating each landmark on the first modeled tissue structure. The processor identifies locations on the image of the first tissue structure for each landmark on the first modeled tissue structure. The landmarks on the first modeled tissue structure are mapped to the locations identified on the image of the first tissue structure.

A sectioning system includes a chuck assembly configured to receive a tissue block, a cutting assembly configured to remove a tissue section from the tissue block, at least one sensor configured to sense data regarding dynamics of one or more components of at least one of the chuck assembly or the cutting assembly, and a control system. The control system is configured to receive data from the at least one sensor, determine whether the data from the at least one sensor shows normal behavior of the one or more components of at least one of the chuck assembly or the cutting assembly, and output a signal if it is determined the data from the at least one sensor does not show normal behavior of the one or more components.

A system includes an image sensor, an imaging pipeline, and a display device. The image sensor is configured to capture a first frame of pixel data. The imaging pipeline is coupled to the image sensor to receive the first frame of pixel data. The imaging pipeline includes an adaptive noise filter. The adaptive noise filter is configured to filter a pixel based on noise in the pixel. The imaging pipeline is configured to output a second frame of pixel data. The second frame of pixel data includes pixels filtered by the adaptive noise filter. The display device is coupled to the imaging pipeline to receive the second frame of pixel data. The display device is configured to display the second frame of pixel data.

With a diagnostic imaging support apparatus, a diagnostic imaging support method, and a diagnostic imaging support program, an optimum image for extracting a contour can be automatically selected from a superimposed image obtained by superimposing a plurality of images of different types. A diagnostic imaging support apparatus 1 includes: an accepting unit 22 that accepts a specification of the position of a predetermined defined region R on a superimposed image G obtained by superimposing a plurality of images of different types including a target image G0 that is a target on which a contour is created; a selection unit 23 that selects an image for extracting a contour on the basis of image information about regions R0, R1, and R2, in the plurality of images of different types, each corresponding to the accepted defined region R; and a contour extraction unit 24 that extracts the contour from the selected image.