Abstract: One or more example embodiments of the present invention relates to a method for providing a virtual, noncontrast image dataset of a patient comprising providing a multiphase CT angiography image dataset of the patient, the multiphase CT angiography image dataset comprising at least three CT image datasets that map an imaging area of the patient at three different points in time relative to an administration of a contrast agent; forming a minimum intensity image dataset of the imaging area based on the at least three CT image datasets, an image value of an image point of the minimum intensity image dataset is in each case based on a minimum value from among image values of the image point, locally corresponding in the imaging area, in the at least three CT image datasets; and outputting of the virtual, noncontrast image dataset based on the minimum intensity image dataset.

Abstract: One or more example embodiments of the invention relates in one aspect to a computer-implemented method for providing a stroke information. The method includes receiving examination data, the examination data comprising computed tomography imaging data of an examination area of a patient, the examination area of the patient comprising at least one brain region, the at least one brain region being affected by a stroke; adjusting a causal model based on the computed tomography imaging data to obtain an adjusted causal model, wherein the adjusted causal model models a first variable as a first cause for an appearance of the examination area of the patient; receiving a first value for the first variable; generating the stroke information based on the adjusted causal model and the first value for the first variable; and providing the stroke information.

Abstract: A method for generating training data for training a deep learning algorithm, comprising: receiving medical imaging data of an examination area including a first part and a second part of a symmetric organ; splitting the medical imaging data along a symmetry plane or a symmetry axis into a first dataset and a second dataset, wherein the first dataset includes the medical imaging data of the first part and the second dataset includes the medical imaging data of the second part; mirroring the second dataset along the symmetry plane or the symmetry axis; generating the training data by stacking the first dataset and the mirrored second dataset; and providing the training data.

Abstract: A computer implemented method maps a three-dimensional branched tubular structure depicted in a three-dimensional image data set into at least one two-dimensional image plane.

Abstract: At least one example embodiment relates to a computer-implemented method for providing stroke information, the method comprising receiving computed tomography imaging data of an examination area of a patient, the examination area of the patient comprising a plurality of brain regions, at least one brain region of the plurality of brain regions being affected by a stroke, receiving brain atlas data, generating registered imaging data based on the computed tomography imaging data and the brain atlas data, the registered imaging data being registered to the brain atlas data, generating the stroke information regarding the stroke based on a set of algorithms and the registered imaging data, and providing the stroke information.

Abstract: 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.

Abstract: In an embodiment of the invention, a plurality of images of a region under examination are recorded at different times. Anatomical information and flow information are derived from the images. The anatomical information may relate to the course of vessels or the structure of perfused tissue. The temporal component of the flow information can advantageously be combined with the anatomical information in a resultant image. An intensity-dependent fenestration assigns a gray-scale value to pixels of the resultant image in accordance with the anatomical information. A time-dependent fenestration assigns a chromaticity to the pixels of the resultant image in accordance with the flow information and the gray-scale values and the chromaticities are assigned independently of one another.

Abstract: In an embodiment of the invention, a plurality of images of a region under examination are recorded at different times. Anatomical information and flow information are derived from the images. The anatomical information may relate to the course of vessels or the structure of perfused tissue. The temporal component of the flow information can advantageously be combined with the anatomical information in a resultant image. An intensity-dependent fenestration assigns a gray-scale value to pixels of the resultant image in accordance with the anatomical information. A time-dependent fenestration assigns a chromaticity to the pixels of the resultant image in accordance with the flow information and the gray-scale values and the chromaticities are assigned independently of one another.

Abstract: A method is disclosed for processing measurement data from perfusion computed tomography, in which both perfusion parameters, in order to calculate which arterial and venous TACs are generated, and dynamic CTA images are generated from the measurement data. In at least one embodiment of the proposed method, averaging is performed over the dynamic CTA images from a plurality of temporally successive time phases in order to obtain averaged CTA images, wherein the time phases over which averaging is performed are determined from the arterial or venous TAC(s). In some cases, the method can dispense with an additional static CTA and so the amount of the injected contrast agent and the radiation dose can be reduced.

Abstract: A method and system for multi-atlas segmentation brain structures and vessel territories in a brain computed tomography (CT) image is disclosed. Each of a plurality of atlas images is individually registered to an input brain CT image, resulting in a plurality of warped atlas images. A region of interest is defined based on labeled brain structures in each of the plurality of warped atlas images. For each atlas image, a respective sum of squared difference (SSD) value is calculated between the corresponding warped atlas image and the brain CT image within the region of interest defined for the corresponding warped atlas image. A number of the atlas images are selected based on the SSD values calculated for the atlas images. The brain structures and vessel territories are segmented in the brain CT image using only the selected atlas images.

Abstract: A method and system for multi-atlas segmentation brain structures and vessel territories in a brain computed tomography (CT) image is disclosed. Each of a plurality of atlas images is individually registered to an input brain CT image, resulting in a plurality of warped atlas images. A region of interest is defined based on labeled brain structures in each of the plurality of warped atlas images. For each atlas image, a respective sum of squared difference (SSD) value is calculated between the corresponding warped atlas image and the brain CT image within the region of interest defined for the corresponding warped atlas image. A number of the atlas images are selected based on the SSD values calculated for the atlas images. The brain structures and vessel territories are segmented in the brain CT image using only the selected atlas images.

Abstract: A method is disclosed for detecting movements and correcting movements in tomographic and projective image series. Further, a tomography or projection system is further disclosed for implementing this method. In at least one embodiment, the temporal changes in an image series with a multiplicity of temporally subsequent image data records are determined and a transformation function for correcting movements is calculated using registration methods, by which movements can be eliminated. To this end, in at least one embodiment a motion detection algorithm recognizes and distinguishes scan volumes and times at which a movement or no movement occurs. Subsequently, in at least one embodiment an algorithm for correcting the movement in those scan volumes in which a movement was detected is implemented, with the correction referring to respectively representative image intervals.

Abstract: A method is disclosed for processing measurement data from perfusion computed tomography, in which both perfusion parameters, in order to calculate which arterial and venous TACs are generated, and dynamic CTA images are generated from the measurement data. In at least one embodiment of the proposed method, averaging is performed over the dynamic CTA images from a plurality of temporally successive time phases in order to obtain averaged CTA images, wherein the time phases over which averaging is performed are determined from the arterial or venous TAC(s). In some cases, the method can dispense with an additional static CTA and so the amount of the injected contrast agent and the radiation dose can be reduced.

Abstract: A method is disclosed for detecting movements and correcting movements in tomographic and projective image series. Further, a tomography or projection system is further disclosed for implementing this method. In at least one embodiment, the temporal changes in an image series with a multiplicity of temporally subsequent image data records are determined and a transformation function for correcting movements is calculated using registration methods, by which movements can be eliminated. To this end, in at least one embodiment a motion detection algorithm recognizes and distinguishes scan volumes and times at which a movement or no movement occurs. Subsequently, in at least one embodiment an algorithm for correcting the movement in those scan volumes in which a movement was detected is implemented, with the correction referring to respectively representative image intervals.

Abstract: In a method and apparatus for the three-dimensional presentation of an examination region of a patient in the form of a 3D reconstruction image, a preoperatively acquired 3D image dataset of the examination region is employed in a medical procedure, datasets representing a number of 2D ultrasound images of the examination region are acquired, the preoperative 3D image dataset is updated using the datasets representing 2D ultrasound images, and the 3D reconstruction image is generated on the basis of the updated 3D image dataset.

Abstract: A method for the positionally correct assignment of two medical image data records of an object is disclosed. In at least one embodiment of the method, at least two partial regions corresponding with respect to the object are respectively selected in the two image data records. Further, a local measure is determined in each partial region for the positional deviation of the two image data records. Finally, the two image data records in the partial region are displaced rigidly relative to one another for each partial region whose local measure exceeds a local limit value.

Abstract: In the borders of a computer-aided presentation method for a 3D subject, a 2D basic image of a subject and a 2D basic presentation of a 3D volume data set of the subject are determined by a computer and momentarily output as images via an output system. The basic image and the basic presentation are thereby simultaneously output by the computer, but spatially separate from one another.

Abstract: In a method for producing an image sequence on the basis of two volume datasets that were acquired at different points in time, a first set of deformation vectors is determined that maps image contents of the first volume dataset onto image contents of the second volume datasets, subsequently a second set of deformation vectors is determined that maps image contents of the second volume dataset onto image contents of the first volume dataset. Subsequently, sets of intermediate volume datasets are produced using attenuated deformation vectors with deformation factors Ai and Bi. Dependent on the size of the deformation factors, the image information of the individual intermediate volume datasets are shifted to different degrees in relationship to the corresponding volume dataset. Subsequently, a set of dissolve volume datasets is produced and displayed as an image sequence.

Abstract: A device for generating fusion images by fusioning two images, in particular medical images, comprising an image-processing computation unit (2) for fusioning the images, as well as a monitor (3) connected thereto for image output, a gray-value histogram (7, I, II) being displayable on the monitor (3) for each image of the images to be fusioned, which device is designed in such a way that, in each gray-value histogram (7, I, II) of the images to be fusioned, one or more gray-value ranges can be selected by user-controlled highlighting of one or more markings (8) on the monitor (3), as well as for generating the fusion image with the aid of the selected gray-value ranges.

Abstract: In a medical treatment/examination device and method for the acquisition and presentation of a medical instrument introduced into a cavity organ of a patient to be examined or treated, particularly in the framework of a cardial examination or treatment with a catheter, intracorporeal registration of 2D ultrasound images of the cavity organ is undertaken using a catheter-like ultrasound acquisition device guided into the cavity organ with simultaneous acquisition of the spatial position and orientation of a 2D ultrasound image by a position acquisition system, a 3D ultrasound image dataset is generated from the 2D ultrasound image, following introduction of the instrument, the instrument is acquired in a coordinate system registered with the 3D ultrasound image dataset, and a 3D reconstruction image is generated on the basis of the 3D image dataset and is presented at a monitor, containing a positionally exact presentation of the instrument in the 3D reconstruction image.