In a method and an evaluation device for the evaluation of projection data of an object being examined, which are determined along a trajectory in a multiplicity of projection positions relative to a co-ordinate origin, a particular trajectory function is determined for the projection positions, for each of a multiplicity of positions from a reconstruction region of dimension n by establishing an offset (d) and a direction vector at the co-ordinate origin, establishing a hyperplane of dimension n−1 which runs perpendicular to the direction vector and has an offset to the co-ordinate origin, establishing a number of intersection points where the hyperplane intersects the trajectory, establishing a derivative vector of the trajectory according to its trajectory path and calculating the derivative vector in the projection position, and establishing an absolute value of a scalar product between the derivative vector and the position and dividing the absolute value by the number. The determined trajectory functions are transformed to a frequency domain of dimension n and the projection data are evaluated by means of the transformed trajectory functions.

A system and method are provided for the reconstruction of medical image data using filtered backprojection with the use of a wavelet transformation. A filter function is applied to at least one part of an object using projection data captured with a detection device prior to backprojection.

A method for processing an X-ray computed tomography (CT) image using a neural network and an apparatus therefor are provided. An image reconstruction method includes receiving low-dose X-ray CT data, obtaining an initial reconstruction image for the received low-dose X-ray CT data using a predetermined analytic algorithm, and reconstructing a denoised final image using the obtained initial reconstruction image and a previously trained neural network.

A 3D image generation method includes controlling a G-arm frame to rotate to a target angle, and keeping the currents and voltages of two X-ray tubes unchanged during rotation, obtaining groups of 2D projection data of an object when a G-arm is in different angles, each group of 2D projection data including two paths of projection data, conducting calculation according to an FDK algorithm or an FDK correction algorithm using the groups of 2D projection data to obtain a 3D image of the object, and outputting the 3D image, thereby greatly reducing the data obtaining time by obtaining two paths of projection data, effectively reducing the irradiation time of the object, directly outputting the 3D image of the object, reflecting the full view information about the object, and solving the problem in the prior art that the irradiation time of the object under examination of X-rays is long.

An apparatus for determining a contour of a treatment region in a patient includes a computer processor to receive input regarding a contour of at least one organ-at-risk (OAR) adjacent to the treatment region; receive input regarding an initial contour of the treatment region; predict a radiation toxicity to the at least one OAR based on the contour of the at least one OAR, the initial contour of the treatment region, and a radiation treatment regimen; determine whether the predicted radiation toxicity exceeds a threshold; and determine a contour of the treatment region by iteratively modifying the initial contour of the treatment region, and any subsequent modified contours of the treatment region, until a stopping condition is satisfied. The stopping condition can be a preselected number of iterations or that the predicted radiation toxicity using the contour in place of the initial contour is first calculated is below said threshold.

A method includes re-sampling current image data representing a reference motion state into a plurality of different groups, each group corresponding to a different motion state of moving tissue of interest, forward projecting each of the plurality of groups, generating a plurality of groups of forward projected data, each group of forward projected data corresponding to a group of the re-sampled current image data, determining update projection data based on a comparison between the forward projected data and the measured projection data, grouping the update projection data into a plurality of groups, each group corresponding to a different motion state of the moving tissue of interest, back projecting each of the plurality of groups, generating a plurality of groups of update image data, re-sampling each group of update image data to the reference motion state of the current image, and generating new current image data based on the current image data and the re-sampled update image data.

A system and method for generating a parametric map of a subject's brain includes receiving non-contrast computed tomography (NCCT) imaging data and receiving computed tomography perfusion (CTP) data. The method further includes creating a baseline image by utilizing the NCCT data and generating a parametric map using the CTP data and the baseline image.

According to one embodiment, a radiation image diagnostic apparatus includes a gantry and image reconstruction circuitry. The gantry images a subject with radiation over a plurality of phases and acquires a plurality of imaging data sets for the plurality of phases. The image reconstruction circuitry executes an iterative reconstruction for the plurality of imaging data set to generate a plurality of reconstruction images for the plurality of phases. The image reconstruction circuitry executes the iterative reconstruction using, as the initial image, the first reconstruction image obtained by executing the iterative reconstruction based on the imaging data set of the first phase, generating a second reconstruction image for the second phase different from the first phase.

The present disclosure relates to image reconstruction with favorable properties in terms of noise reduction, spatial resolution, detail preservation and computational complexity. The disclosed techniques may include some or all of: a first-pass reconstruction, a simplified datafit term, and/or a deep learning denoiser. In various implementations, the disclosed technique is portable to different CT platforms, such as by incorporating a first-pass reconstruction step.

Systems and methods of enhanced display and viewing of three dimensional (3D) tomographic data acquired in tomosynthesis or tomography. A set of projection data is acquired with an image acquisition system and used to reconstruct enhanced 3D volume renderings that are viewed with motion, advanced image processing or stereotactically to assist in medical diagnosis. Various enhancements are provided for further processing the images, thereby providing additional features and benefits during image viewing.