A neural network is trained for estimating patient hemodynamic data using a plurality of extravascular imaging data sets and a plurality of intravascular imaging data sets that are each co-registered to a corresponding extravascular imaging data set. A plurality of hemodynamic data sets are provided, each hemodynamic data set co-registered with the corresponding extravascular imaging data set. The neural network learns what hemodynamic data to expect for a given intravascular imaging data set. An intravascular imaging event is subsequently performed in which an intravascular imaging element is translated within a blood vessel of the patient to produce one or more intravascular images. The neural network uses its training to predict hemodynamic values corresponding to the one or more intravascular images from the intravascular imaging event, and the one or more intravascular images are outputted in combination with the predicted hemodynamic values.

One or more example embodiments of the present invention relates to a method for providing vessel wall-related data. The method includes receiving spectral computed tomography data of an examination region, the examination region having a vessel; calculating a representation of a vessel wall of the vessel and at least one parameter map of the examination region based on the spectral computed tomography data; calculating the vessel wall-related data based on the representation of the vessel wall and the at least one parameter map of the examination region; and providing the vessel wall-related data.

The present disclosure provides medical devices and methods thereof. The medical device may include a housing, a positron emission tomography (PET) detector module, and a radio frequency (RF) coil. The housing may form a scanning tunnel for accommodating a subject. The PET detector module may be arranged along a circumference of the scanning tunnel. The RF coil may be arranged along the circumference of the scanning tunnel. The RF coil may include a first RF coil and a second RF coil. The first RF coil and the second RF coil may be disposed coaxially around an axial direction of the scanning tunnel. A projection of the second RF coil along a radial direction of the scanning tunnel may cover at least a portion of a gap of the first RF coil.

A tissue mapping system includes: an imaging stylet, a stylet-deploying mechanism, and a system console with data-processing capability. This tissue mapping system calculates, in-real time, a position of the stylet during tissue imaging and sensing. This position is then used to combine and re-map image and sensor data acquired by the stylet from different regions of the mapped tissue. The stylet is configured to acquire image data within its vicinity when inserted in a tissue, and also has a sensing region along a flexible distal portion of its length. The stylet-deploying mechanism inserts the stylet in different regions of the mapped tissue iteratively. The stylet-deploying mechanism also incorporates features for registering the position of the stylet by using strain sensing or image data. The system console communicates with the stylet to calculate the position of the stylet by using intra-operative tissue image data and distributed strain data within the sensing region of the stylet. The stylet incorporates optical guides that are advantageously used both for imaging and for distributed strain sensing. Another aspect of the invention is the use of the very same imaging and strain sensing optical guide to interrogate biochemical sensors disposed distally within the stylet in some embodiments.

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.

A radiation image display apparatus that constitutes a radiation imaging system includes a displayer and a hardware processor that acquires image data of a dynamic image constituted of a plurality of frame images, image data of an analysis dynamic image obtained by applying predetermined image processing to the image data of the dynamic image and image data of a related dynamic image which is related to the dynamic image or the analysis dynamic image respectively, and causes the displayer to display the related dynamic image together with the dynamic image and the analysis dynamic image.

A method includes generating first contrast significance data for a first computer vision model generated from a first training set of medical scans. First significant contrast parameters are identified based on the first contrast significance data. A first re-contrasted training set is generated based on performing a first intensity transformation function on the first training set of medical scans, where the first intensity transformation function utilizes the first significant contrast parameters. A first re-trained model is generated from the first re-contrasted training set, which is associated with corresponding output labels based on abnormality data for the first training set of medical scans. Re-contrasted image data of a new medical scan is generated based on performing the first intensity transformation function. Inference data indicating at least one abnormality detected in the new medical scan is generated based on utilizing the first re-trained model on the re-contrasted image data.

A method of treating a human patient identified as having an injury to a body region includes receiving CT images, where the CT images were generated by performing a CT angiography of an injured body region of the human patient. The method further includes determining, based on the CT images, a total volumetric rate of active bleeding in the injured body region; and recommending at least one treatment approach for the human patient based on the total volumetric rate of active bleeding.

A method for gating in tomographic imaging system includes steps of: (a) performing a tomographic imaging on an object with a target moving periodically along a first axis for acquiring projection images; (b) obtaining projected curves by summing up pixel values along a direction of a second axis perpendicular to the first axis in each projection image; (c) determining a target zone on the projection images, wherein a central position on the first axis of the target zone is corresponding to a position having the largest variation in the projected curves on the first axis; (d) calculating parameter values of pixel values in the target zones and obtaining a curve of a moving cycle of the target according to the parameter values; and (e) selecting the projection images under the same state in the moving cycle for image reconstruction according to the curve of the moving cycle of the target.