Siemens Healthcare Gmbh

Siemens Healthineers Ag

Markus Juergens

Florian Thamm

Karl Stierstorfer

Bernhard Schmidt

Bernhard Krauss

Eric Fournie

Hendrik Ditt

A computer-implemented segmentation method for segmenting a core and a penumbra in a four-dimensional computed tomography perfusion dataset of ischemic tissue in an image region of a patient, includes determining at least one parameter map for at least one perfusion parameter from the computed tomography perfusion dataset; and using the at least one parameter map and the computed tomograph perfusion dataset as input data to a trained function to determine output data, the output data including segmentation information of the penumbra and the core.

Computer-implemented segmentation and training method in computed tomography perfusion, segmentation and training system, computer program and electronically readable storage medium

A method and system are for analyzing a plurality of interconnected blood vessels, preferably for providing output data for the analysis of a plurality of interconnected blood vessels, e.g. for vessel segmentation, vessel labeling, and vessel occlusion detection. The output data include a graphical representation of a vessel tree model of a patient. The method of an embodiment, in the most general terms includes receiving input data, e.g. via an interface; generating output data by applying algorithmic operations to the input data; and providing the output data, e.g. via an interface.

Method and system for analyzing a plurality of interconnected blood vessels

In an embodiment of a motion correction method, a first virtual non-contrast X-ray image of a region under examination is determined based upon first spectral raw X-ray data associated with a first contrast distribution, via material decomposition. In addition, a second virtual non-contrast X-ray image of the region under examination is determined based upon second spectral raw X-ray data associated with a second contrast distribution, differing from the first contrast distribution, via material decomposition. Then the first virtual non-contrast X-ray image is registered with the second virtual non-contrast X-ray image to determine a transformation field between the two virtual non-contrast X-ray images. Finally, based upon the determined transformation field, first X-ray image data based on the first raw X-ray data is registered with second X-ray image data based on the second raw X-ray data. An X-ray imaging method, a motion correction device and an X-ray imaging system are also discussed.

Motion correction method

To generate images, in which a first row area of a multiple-row detector is illuminated with a first X-ray spectrum and a second row area of the multiple-row detector, trailing in the direction of travel, is illuminated with a second X-ray spectrum, image data is recorded at a pitch chosen such that one slice image can be reconstructed in each case for a sectional position for the first and the second row area. Correspondingly, for the sectional position, the respective slice image for the first and the second row area is reconstructed. For a third row area, illuminated with the first and the second X-ray spectrum, a reference sectional image is reconstructed as a slice image. To generate motion-reduced first and second spectral images assigned to the first and second row area respectively, the slice images of the first and second row areas are registered to the reference sectional image.

Growing community of inventors

Adelsdorf, Germany

Markus Juergens