Techniques for compensating magnetic resonance imaging (MRI) data for artefacts caused by motion of a subject being imaged. The techniques include obtaining spatial frequency data obtained by using a magnetic resonance imaging (MRI) system to perform MRI on a patient, the spatial frequency data including first spatial frequency data and second spatial frequency data; determining a transformation using a first image obtained using the first spatial frequency data and a second image obtained using the second spatial frequency data; determining a residual spatial phase; correcting, using the transformation, second spatial frequency data and the residual spatial phase, to obtain corrected second spatial frequency data and a corrected residual spatial phase; and generating a magnetic resonance (MR) image using the corrected second spatial frequency data and the corrected residual spatial phase.

There are provided techniques for analyzing an atom probe tomography data set obtained from a tip-shaped sample. The techniques include defining analysis sub-volumes in the atom probe tomography data set; performing a fast Fourier transform (FFT) on each of the analysis sub-volumes to obtain a signal in a Fourier domain; identifying at least one FFT peak in the signal in the Fourier domain, each FFT peak being indicative of an expected crystal feature in the corresponding analysis sub-volume; continuously and automatically calculating an image compression factor and a radius of the tip-shaped sample, based on identified crystal features, the identified crystal features being obtained from a collection of expected crystal features; and reconstructing a three-dimensional model of the tip-shaped sample. Said reconstructing includes comparing the identified crystal features with calibration data; and dynamically adjusting the image compression factor and the radius of the tip-shaped sample.

In some embodiments, the present specification describes methods for displaying a three-dimensional image of an isolated threat object or region of interest with a single touch or click and providing spatial and contextual information relative to the object, while also executing a view dependent virtual cut-away or rendering occluding portions of the reconstructed image data as transparent. In some embodiments, the method includes allowing operators to associate audio comments with a scan image of an object. In some embodiments, the method also includes highlighting a plurality of voxels, which are indicative of at least one potential threat item, in a mask having a plurality of variable color intensities, where the intensities may be varied based on the potential threat items.

A deep neural network for metal artifact reduction is described. A method for computed tomography (CT) metal artifact reduction (MAR) includes generating, by a projection completion circuitry, an intermediate CT image data based, at least in part, on input CT projection data. The intermediate CT image data is configured to include relatively fewer artifacts than an uncorrected CT image reconstructed from the input CT projection data. The method further includes generating, by an artificial neural network (ANN), CT output image data based, at least in part, on the intermediate CT image data. The CT output image data is configured to include relatively fewer artifacts compared to the intermediate CT image data. The method may further include generating, by detail image circuitry, detail CT image data based, at least in part, on input CT image data. The CT output image data is generated based, at least in part, on the detail CT image data.

A method for rendering metal obscured regions in a volume radiographic image reconstructs a first 3D image using a plurality of 2D projection images obtained over a scan angle range relative to the subject and identifies metal in the first 3D image or metal shadows in the plurality of 2D projection images. Then, metal obscured regions are determined in a reconstructed 3D image of the object, and an alternative reconstruction being a limited angle reconstruction is performed for the metal obscured regions and displayed to the user with an indication of the spatial relationship to a corresponding metal obscured region.

In a radiation therapy system, treatment X-rays are delivered to a target volume at the same time that imaging X-rays are also delivered to the target volume for generating image data of the target volume. That is, during an imaging interval in which imaging X-rays are delivered to the target volume, one or more pulses of treatment X-rays are also delivered to the target volume. In each pixel of an X-ray imaging device of the radiation therapy system, image signal is accumulated during portions of the imaging interval in which only imaging X-rays are delivered to the target volume and is prevented from accumulating in each pixel during the pulses of treatment X-rays.

In some embodiments, noise data may be used to train a neural network (or other prediction model). In some embodiments, input noise data may be obtained and provided to a prediction model to obtain an output related to the input noise data (e.g., the output being a prediction related to the input noise data). One or more target output indications may be provided as reference feedback to the prediction model to update one or more portions of the prediction model, wherein the one or more portions of the prediction model are updated based on the related output and the target indications. Subsequent to the portions of the prediction model being updated, a data item may be provided to the prediction model to obtain a prediction related to the data item (e.g., a different version of the data item, a location of an aspect in the data item, etc.).

The invention relates to a method for determining the position of a surgical tool relative to a target volume inside an animal body according to a pre-plan comprising the steps of i) obtaining a plurality of two-dimensional images of said target volume using imaging means, each 2D-image being represented by an image data slice I(x,y,z); ii) reconstructing from said plurality of image data slices I(x,y,z) a three-dimensional image of said target volume using transformation means, said 3D-image being represented by a volumetric image data array V(x,y,z); iii) displaying said three-dimensional image of said target volume to an user using displaying means.

A method displays spectral image data reconstructed from spectral projection data with a first reconstruction algorithm and segmented image data reconstructed from the same spectral projection data with a different reconstruction algorithm, which is different from the first reconstruction algorithm. The method includes reconstructing spectral projection data with the first reconstruction algorithm, which generates the spectral image data and displaying the spectral image data. The method further includes reconstructing the spectral projection data with the different reconstruction algorithm, which generates segmentation image data, segmenting the segmentation image data, which produces the segmented image data, and displaying the segmented image data.

A method for controlling a medical device may be provided. The method may include obtaining, via one or more cameras, first data regarding a first motion of a subject in an examination space of the medical device. The method may include obtaining, via one or more radars, second data regarding a second motion of the subject. The method may further include generating, based on the first data and the second data, a control signal for controlling the medical device to scan at least a part of the subject.