Siemens Healthcare Gmbh

Siemens Healthineers Ag

Michael Manhart

Markus Kowarschik

Christian Kaethner

Alexander Preuhs

Günter Lauritsch

Annette Birkhold

Holger Kunze

Christopher Rohkohl

Michael Zellerhoff

Thomas Brunner

Sebastian Bauer

Björn Kreher

Peter Fischer

Julie DiNitto

Manuela Meier

Tristan Gottschalk

Yixing Huang

Michele Kiessling

A computer-implemented method for determining a subtraction image from a feature image and a plurality of mask images of an imaging area of an examination object is provided. A combination of the plurality of mask images weighted by mask weights is subtracted from the feature image to determine the subtraction image. The mask weights are determined in an optimization process for optimizing an image quality function for test images calculated by subtracting a combination of the mask images determined with a test set of mask weights from the feature image. The image quality function is minimized in the form of a convex quadratic program of a dimension corresponding to the number of mask images.

Computer-implemented method for determining a subtraction image, image recording facility, computer program, and electronically readable data carrier

A method for controlling a C-arm of a C-arm system includes performing a forward leg of a rotation of the C-arm, wherein the forward leg starts at a start position of the forward leg of the C-arm with a lateral offset having a first offset value, and the C-arm is rotated in the forward direction as far as an end position of the forward leg, with the lateral offset being reduced to 0. In addition, a return leg of a rotation of the C-arm is performed, wherein the return leg starts at the end position of the forward leg, and the C-arm is rotated in the return direction as far as an end position of the return leg, with the lateral offset being increased in the opposite direction to the lateral offset of the forward leg up to a second offset value at the end position of the return leg.

Trajectory of a C-arm of a C-arm system

A method includes receiving image data of an examination object. A first temporary data record is created by applying a first correction to the image data. A further temporary data record is created by applying a further correction to the image data. The further correction at least partially corresponds to the first correction. A trained function is applied to input data that is based on the first temporary data record and the further temporary data record. A parameter of the trained function is based on an image quality metric. It is determined whether the first temporary data record has a higher image quality compared with the further temporary data record. When a result is positive, the first temporary data record is provided as the corrected medical image data. When the result is negative, the further temporary data record is provided as the image data, and part of the method is repeated.

Provision of corrected medical image data

For creation of a movement-compensated image reconstruction in an x-ray based imaging method an optimal object movement trajectory is determined by application of a trained algorithm to an optimal latent vector and the movement-compensated image reconstruction is created depending on projection images, with the assumption that the object would have moved in accordance with the optimal object movement trajectory while the imaging method was being carried out. The optimal latent vector is determined by a predetermined cost function being minimized using the latent vector as an optimization parameter, wherein for each optimization step with a current latent vector, a current object movement trajectory is determined by application of a trained algorithm to the current latent vector, and a current value of the cost function is computed depending on the plurality of projection images, with the assumption that the object would have moved in accordance with the current object movement trajectory while the imaging method was being carried out.

Movement-compensated image reconstruction for an x-ray based imaging method

A method for generating a subtraction image for digital subtraction angiography to reduce noise and movement artifacts. Obtaining a plurality of mask images of an object takes place before administering a contrast agent into the object and obtaining a map of the object after administering a contrast agent into the object. A first sum image is obtained from the plurality of mask images in that the plurality of mask images is summed in each case multiplied by an individual weighting. The individual weightings for each of the plurality of mask images are automatically determined by an optimization method, and the subtraction image is ascertained by subtraction of the sum image from the map.

Optimum weighting of DSA mask images

A computer-implemented method is for the correction of streak artifacts in slice images. In an embodiment, the method includes: receiving at least one initially reconstructed slice image by a processor, the at least one initially reconstructed slice image being based on a plurality of initial projection images; determining at least one variation slice image, via the processor, using a variation algorithm, the at least one variation slice image being based on the at least one initially reconstructed slice image; determining at least one variation projection image based upon the at least one variation slice image; and determining at least one corrected slice image as a function of the at least one variation projection image.

Streak artifact correction

A computer-implemented method comprises: providing at least two exploratory views; segmenting a first object in the at least two exploratory views to determine first two-dimensional object masks; segmenting the second object in the at least two exploratory views tow determine second two-dimensional object masks; determining a first three-dimensional object mask as a function of the first two-dimensional object masks; determining a second three-dimensional object mask as a function of the second two-dimensional object masks; and determining an overlap of the first object and the second object for at least one capture trajectory as a function of the first three-dimensional object mask and the second three-dimensional object mask.

Method for defining a capture trajectory

A method for providing an optimum subtraction data set includes receiving first image data sets that are recorded by a medical imaging device and map an examination object within a first temporal phase. At least one second image data set that maps the examination object within a second temporal phase and is recorded by the same or another medical imaging device is received. Mask data sets are determined. The mask data sets include at least one of the first image data sets and/or an averaging of at least one combination of the first image data sets. Subtraction data sets are generated by subtracting one of the mask data sets from the at least one second image data set, and an image quality parameter is determined for each of the subtraction data sets. An optimum subtraction data set is provided by a comparison of the image quality parameters.

Provision of an optimum subtraction data set

A computer-implemented method for providing a vascular image data record includes receiving a plurality of projection-X-ray images recorded in temporal succession. The plurality of projection-X-ray images at least partially map a common examination region of an examination object. The plurality of projection-X-ray images map a temporal change in the examination region of the examination object. A change image data record is determined in each case based on at least one region of interest of the plurality of projection-X-ray images. The at least one region of interest includes a plurality of image points. The change image data record in each case includes a time-intensity curve for each of the image points. The vascular image data record is generated based on the change image data record, and the vascular image data record is provided.

Providing a vascular image data record

First projection images are recorded. The first projection images map an examination object along different first projection directions. A corresponding respective second projection image is recorded for at least two first projection images. The first projection images each have a first focus point, and the second projection images each have a second focus point. Each of the second projection images together with a corresponding first projection image at least partially map a common part of the examination object about a stationary center point. The second projection images map the examination object along second projection directions that are mutually different and at least partially different, relative to the respectively corresponding first projection directions such that a straight line through the first focus point and the second focus point of the mutually corresponding first projection images and second projection images extends through the stationary center point. The 3D image dataset is reconstructed.

Providing a 3D image dataset of an examination object

Systems and methods for quantification of an influence of scattered radiation in the analysis of an object a projection image is provided. Based on the projection image and on a characteristic of a tomography facility and/or of the object relating to the influence of the scattered radiation, at least one intermediate image is created. The at least one intermediate image is analyzed using an artificial neural network to quantify the influence of the scattered radiation.

Quantification of an influence of scattered radiation in a tomographic analysis

A computer-implemented method is for providing a difference image data record. In an embodiment, the method includes a determination of a first real image data record of an examination volume in respect of a first X-ray energy, and a determination of a multi-energetic real image data record of the examination volume in respect of a first X-ray energy and a second X-ray energy, the second X-ray energy differing from the first X-ray energy. The method further includes the determination of the difference image data record of the examination volume by applying a trained function to input data, wherein the input data is based upon the first real image data record and the multi-energetic real image data record, as well as the provision of the difference image data record.

Providing a difference image data record and providing a trained function

A computer-implemented method for reconstruction of medical image data includes receiving medical measuring data, and minimizing a cost value via gradient descent. Minimizing the cost value includes: reconstructing the medical image data by applying a reconstruction function to the received medical measuring data in accordance with reconstruction parameters; determining a cost value by applying a cost function to the reconstructed medical image data; determining a gradient of the cost function with respect to the reconstruction parameters; adjusting the reconstruction parameters based on the gradient of the cost function with respect to the reconstruction parameters and the previous reconstruction parameters; and providing the adjusted reconstruction parameters. The acts of the minimizing are repeated until a termination condition is met. The reconstructed medical image data is provided.

Computer-implemented method for the reconstruction of medical image data

A method for providing an optimum subtraction data set includes: receiving first image data sets acquired by a medical imaging device and which map an object under examination within a first time phase; receiving at least one second image data set acquired by the same or another medical imaging device and which maps a change in the object under examination within a second time phase; dividing the at least one second image data set into a plurality of image regions; generating subtraction image regions for the plurality of image regions; determining an image quality parameter for each subtraction image region; determining an optimum subtraction image region for each image region of the plurality of image regions of the at least one second image data set by comparing the image quality parameters; generating the optimum subtraction data set from the optimum subtraction image regions; and providing the optimum subtraction data set.

Providing an optimum subtraction data set

A computer-implemented method includes, in an embodiment, receiving first X-ray projections of an examination volume in respect of a first X-ray energy and second X-ray projections in respect of a second X-ray energy, the first and second X-ray energies differing. The method further includes determination of a multienergetic real image data record of the examination volume based upon the first and second X-ray projections; selection of first voxels of the multienergetic real image data record based upon the multienergetic real image data record; selection of second voxels of the multienergetic real image data record based upon the first X-ray projections and the second X-ray projections, the first voxels including the second voxels and the second voxels mapping contrast medium in the examination volume. The method further includes provision of a constraint image data record and/or a difference image data record based upon the second voxels.

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Fürth, Germany

Michael Manhart