Aspects of the present disclosure relate to systems, devices and methods for performing a surgical step or surgical procedure for example with visual guidance using a head mounted display or with a surgical navigation system or with a surgical robot. A computer processor can be configured to determine the pose of a first vertebra with an attached first marker and a second vertebra with an attached second marker. The computer processor can be configured to determine the pose of at least one vertebra interposed or adjacent to the first and second vertebrae with attached markers, e.g. fiducial markers.

There are described herein methods and system for generating an inspection image of an object from radiographic imaging. The method comprises obtaining a plurality of digital images of the object positioned between a radiation source and a photon beam detector, the digital images taken at different object-detector distances or source-detector distances to create unique grain diffraction patterns in each one of the digital images, and forming the inspection image from image features common to the digital images at a common scale and removing the unique grain diffraction patterns.

An apparatus, method, and computer-readable medium for improving image quality of a medical volume. In an embodiment, the apparatus includes processing circuitry configured to receive a reconstructed input image volume from X-ray projection data corresponding to a three-dimensional region of an object to be examined, apply a pseudo-three-dimensional neural network (P3DNN) to the reconstructed input image volume, the application of the pseudo-three-dimensional neural network including generating, for the reconstructed input image volume, a plurality of three-dimensional image datasets representing a different anatomical plane of the reconstructed input image volume, applying at least one convolutional filter to each of a sagittal plane dataset, a transverse plane dataset, and a coronal plane dataset, and concatenating results of the applied at least one convolutional filter to generate an intermediate output image volume, and generate, based on the application of the P3DNN, an output image volume corresponding to the three-dimensional region of the object.

The present disclosure relates to systems and methods for image storage. The methods may include obtaining a first image of a subject. The methods may further include obtaining a second image of the subject. The second image may include scan status information of the subject. The scan status information may be associated with a status of the subject when the first image is acquired. And The methods may also include storing the second image correspondingly with the first image.

Risk prediction models are trained and deployed to analyze images, such as computed tomography scans, for predicting future risk of lung cancer for one or more subjects. Individual risk prediction models are separately trained on nodule-specific and non-nodule specific features such that each risk prediction model can predict future risk of lung cancer across different time periods (e.g., 1 year, 3 years, or 5 years). Such risk prediction models are useful for developing preventive therapies for lung cancer by enabling clinical trial enrichment.

The invention concerns a method for measuring the dimensions of empty glass containers (2) consisting in: selecting at least one region to be inspected of the container, transporting the containers, positioning, on either side of the region to be inspected, at least one focus of an X-ray generator tube and image sensors, acquiring, using image sensors, for each container during its displacement, at least three radiographic images of the inspected region, analyzing the at least three radiographic images so as to determine the three-dimensional coordinates of a set of points to deduce at least one inner diameter of the neck and/or one thickness of the body.

The present disclosure relates to methods and systems for vascular image processing. The method may include obtaining an initial vascular image, generating a vascular fragment image by performing a vascular fragmentation operation on the initial vascular image, and generating, based on the vascular fragment image, a vascular centerline image.

The present invention relates to a system for determining the number of small products in the bag package from the x-ray image that enables detecting the missing quantities of small products or packages in a disorganized and random position in the bag package.

An apparatus for determining a functional index for stenosis assessment of a vessel is provided. The apparatus comprises an input interface (40) and a processing unit (50). The input interface is configured to obtain image data (30) representing a two-dimensional representation of a vessel (6). The processing unit (50) is configured to determine a course of the vessel (6) and a width (w1, w2) of the vessel along its course in the image data and is further configured to determine the functional index for stenosis assessment of the vessel based on the width of the vessel in the image data.

A method for quantitative flow analysis of a fluid flowing in a conduit from a sequence of consecutive image frames of such a conduit, where such image frames are timely separated by a certain time interval, the method comprising: a) selecting a start image frame and an end image frame from the sequence either automatically or upon user input; b) determining a centerline of the conduit in the start image frame; c) determining a centerline of the conduit in the end image frame; d) selecting a common start point on the centerline of the start image frame and on the centerline of the end image frame either automatically or upon user input; e) selecting an end point on the centerline of the start image frame; f) selecting an end point on the centerline of the end image frame; g) calculating centerline distance between the start point and the end point of the start image frame; h) calculating centerline distance between the start point and the end point of the end image frame; and i) calculating a local flow velocity as a function of the centerline distances of g) and h) and a time interval between the start image frame and the end image frame.
A corresponding imaging device and computer program are also disclosed.