Abstract: The disclosure relates to a method and to an image processing facility configured to carry out the method for the segmentation of image data of a target object. In the method, a first segmentation is generated by a trained algorithm. Furthermore, a statistical shape and appearance model is provided, which is trained on corresponding target objects. An interference region is further determined, in which the image data is impaired by an image artifact. A final segmentation of the image data is then generated by adjusting the shape and appearance model to the respective target object outside the interference region and using the first segmentation in the interference region.

Abstract: A method for increasing accuracy of positioning an X-ray device relative to an examination subject using a camera system includes recording a first data set, acquiring original positioning information pertaining to the X-ray device and specifying a target position of the X-ray device relative to the original position. The X-ray device is positioned out of the original position into a first approach position using the original positioning information, and a second data set is recorded. A deviation between the target position and the first approach position is determined by a reconciliation between the first data set and the second data set. The X-ray device is positioned out of the first approach position into a second approach position using the determined deviation.

Abstract: Evaluating the reliability of a computed tomography (CT) volume image includes acquiring a first CT volume image and a modified CT volume image that are reconstructed from scanned projection images. From the first CT volume image and the modified CT volume image, digitally reconstructed X-ray images are then calculated. A respective similarity with a corresponding one of the scanned projection images is then determined. Based on a comparison of these similarities with one another, the reliability of the CT volume images is then evaluated.

Abstract: A method for segmenting metal objects in projection images acquired using different projection geometries is provided. Each projection image shows a region of interest. A three-dimensional x-ray image is reconstructed from the projection images in the region of interest. A trained artificial intelligence segmentation algorithm is used to calculate first binary metal masks for each projection image. A three-dimensional intermediate data set of a reconstruction region that is larger than the region of interest is reconstructed by determining, for each voxel of the intermediate data set, as a metal value, a number of first binary metal masks showing metal in a pixel associated with a ray crossing the voxel. A three-dimensional binary metal mask is determined. Second binary metal masks are determined for each projection image by forward projecting the three-dimensional binary metal mask using the respective projection geometries.

Abstract: The disclosure relates to a method for recording a panorama dataset of an examination object by a movable medical x-ray device, to a medical x-ray device, and to a computer program product for carrying out the method. The medical x-ray device has an x-ray source, which emits a bundle of x-rays, wherein a first image segment, which maps at least one part of the examination object, is recorded at a first point in time. Position data is acquired, which maps the spatial position of the x-ray device at this first point in time. At least one further image segment along an imaging path is recorded after there has been a movement of the x-ray device, wherein the imaging path lies in one plane, wherein a central ray of the bundle of x-rays emitted by the x-ray source does not run in parallel to the plane in which the imaging path lies. Additionally, position data is acquired, which maps the spatial position of the x-ray device at the time of the recording of the at least one further image segment.

Abstract: A system and method of registration between devices includes a tracking system and a controller. The system is configured to couple to a first device and a second arm separate from the first device. The first device has a first arm configured to couple to a manipulatable device. The second arm is configured to couple to an imaging device. The controller is configured to determine, based on tracking data from the tracking system, a first pose of the first arm and a second pose of the second arm; send a movement command to the second arm that directs the second arm to move into a third pose while maintaining a safety margin between the first and second arms. In the third pose the imaging device can capture an image of at least a portion of the manipulatable device. The movement command is based on the first and second poses.

Abstract: The disclosure relates to a method and to an image processing facility configured to carry out the method for the segmentation of image data of a target object. In the method, a first segmentation is generated by a trained algorithm. Furthermore, a statistical shape and appearance model is provided, which is trained on corresponding target objects. An interference region is further determined, in which the image data is impaired by an image artifact. A final segmentation of the image data is then generated by adjusting the shape and appearance model to the respective target object outside the interference region and using the first segmentation in the interference region.

Abstract: A system and method of dynamic virtual collision objects includes a control unit for a medical device. The control unit includes one or more processors and an interface coupling the control unit to the medical device. The control unit is configured to determine a position of a first movable segment of the medical device, a volume occupied by the first movable segment being approximated by one or more first virtual collision objects (VCOs); adjust, based on the position and motion goals for the medical device, one or more properties of the first VCOs; determine, based on the position and the properties, first geometries of the first VCOs; receive second geometries of one or more second VCOs associated with a second segment of a second device; determine relationships between the first VCOs and the second VCOs; and adjust, based on the relationships, a motion plan for the medical device.

Abstract: A method for establishing a three-dimensional tomosynthesis data record of a target volume from two-dimensional projection images recorded with a recording arrangement including an X-ray source and an X-ray detector in different recording geometries is provided. During or after a reconstruction step, a deconvolution technique is used for reducing image artifacts of the tomosynthesis data record occurring due to lacking information. The projection images are recorded along a linear recording trajectory of the X-ray source. The reconstruction and the use of the deconvolution technique take place in a plurality of different two-dimensional reconstruction planes that are spanned by the recording trajectory and, in each case, a definition point in the target volume.

Abstract: A method for increasing accuracy of positioning an X-ray device relative to an examination subject using a camera system includes recording a first data set, acquiring original positioning information pertaining to the X-ray device and specifying a target position of the X-ray device relative to the original position. The X-ray device is positioned out of the original position into a first approach position using the original positioning information, and a second data set is recorded. A deviation between the target position and the first approach position is determined by a reconciliation between the first data set and the second data set. The X-ray device is positioned out of the first approach position into a second approach position using the determined deviation.

Abstract: The disclosure relates to a method for recording a panorama dataset of an examination object by a movable medical x-ray device, to a medical x-ray device, and to a computer program product for carrying out the method. The medical x-ray device has an x-ray source, which emits a bundle of x-rays, wherein a first image segment, which maps at least one part of the examination object, is recorded at a first point in time. Position data is acquired, which maps the spatial position of the x-ray device at this first point in time. At least one further image segment along an imaging path is recorded after there has been a movement of the x-ray device, wherein the imaging path lies in one plane, wherein a central ray of the bundle of x-rays emitted by the x-ray source does not run in parallel to the plane in which the imaging path lies. Additionally, position data is acquired, which maps the spatial position of the x-ray device at the time of the recording of the at least one further image segment.

Abstract: A method for segmenting metal objects in projection images acquired using different projection geometries is provided. Each projection image shows a region of interest. A three-dimensional x-ray image is reconstructed from the projection images in the region of interest. A trained artificial intelligence segmentation algorithm is used to calculate first binary metal masks for each projection image. A three-dimensional intermediate data set of a reconstruction region that is larger than the region of interest is reconstructed by determining, for each voxel of the intermediate data set, as a metal value, a number of first binary metal masks showing metal in a pixel associated with a ray crossing the voxel. A three-dimensional binary metal mask is determined. Second binary metal masks are determined for each projection image by forward projecting the three-dimensional binary metal mask using the respective projection geometries.

Abstract: A method is provided for operating a medical imaging device when performing an imaging examination. In order to allow an improved preparation of images in the context of such an imaging examination, the method includes: providing an original image of a body region; recording an updated image of the body region; and generating a three-dimensional subsequent image from the original image and from the updated image using a previously trained artificial neural network.

Abstract: Evaluating a reliability of a computed tomography (CT) volume image includes acquiring a first CT volume image and a modified CT volume image that are reconstructed from scanned projection images. From the first CT volume image and the modified CT volume image, digitally reconstructed X-ray images are then calculated. A respective similarity with a corresponding one of the scanned projection images is then determined. Based on a comparison of these similarities with one another, a reliability of the CT volume images is then evaluated.

Abstract: A method is provided for operating a medical imaging device when performing an imaging examination. In order to allow an improved preparation of images in the context of such an imaging examination, the method includes: providing an original image of a body region; recording an updated image of the body region; and generating a three-dimensional subsequent image from the original image and from the updated image using a previously trained artificial neural network.

Abstract: In a method and an apparatus to provide updated images during a robotically-implemented surgical procedure, 3D data is obtained of a volume of a patient, which includes anatomy involved in the procedure. The anatomy is segmented from a reconstructed image of the volume. During the procedure, the surgeon applies forces on the anatomy, causing a geometric change of the anatomy. Force sensors in the surgical robot detect these forces, which are supplied to a processor that controls display of the segmented anatomy at a display screen. From the applied forces and the physical properties of the anatomy, the processor calculates the geometric change of the anatomy that has occurred and modifies the appearance and/or position of the displayed segmented anatomy on the display screen in real time during the procedure, so as to visualize the geometric change.

Abstract: A system and method of registration between devices includes a tracking system and a controller. The system is configured to couple to a first device and a second arm separate from the first device. The first device has a first arm configured to couple to a manipulatable device. The second arm is configured to couple to an imaging device. The controller is configured to determine, based on tracking data from the tracking system, a first pose of the first arm and a second pose of the second arm; send a movement command to the second arm that directs the second arm to move into a third pose while maintaining a safety margin between the first and second arms. In the third pose the imaging device can capture an image of at least a portion of the manipulatable device. The movement command is based on the first and second poses.

Abstract: A system and method for movement control includes a controller coupled to a computer-assisted surgical device having a first movable arm coupled to a manipulatable device having a working end and a second movable arm coupled to an image capturing device. The controller is configured to receive first configurations for the first movable arm; receive second configurations for the second movable arm; receive a plurality of images of the working end from the image capturing device; determine a position and an orientation of the working end; determine a first movable arm position and trajectory for the first movable arm; determine a second movable arm position and trajectory for the second movable arm; determine whether motion of the movable arms will result in an undesirable relationship between the movable arms; and send a movement command to the first or second movable arm to avoid the undesirable relationship.

Abstract: A system and method of dynamic virtual collision objects includes a control unit for a medical device. The control unit includes one or more processors and an interface coupling the control unit to the medical device. The control unit is configured to determine a position of a first movable segment of the medical device, a volume occupied by the first movable segment being approximated by one or more first virtual collision objects (VCOs); adjust, based on the position and motion goals for the medical device, one or more properties of the first VCOs; determine, based on the position and the properties, first geometries of the first VCOs; receive second geometries of one or more second VCOs associated with a second segment of a second device; determine relationships between the first VCOs and the second VCOs; and adjust, based on the relationships, a motion plan for the medical device.

Abstract: A system and method of dynamic virtual collision objects includes a control unit for a medical device. The control unit includes one or more processors and an interface coupling the control unit to the medical device. The control unit is configured to determine a position of a first movable segment of the medical device, a volume occupied by the first movable segment being approximated by one or more first virtual collision objects (VCOs); adjust, based on the position and motion goals for the medical device, one or more properties of the first VCOs; determine, based on the position and the properties, first geometries of the first VCOs; receive second geometries of one or more second VCOs associated with a second segment of a second device; determine relationships between the first VCOs and the second VCOs; and adjust, based on the relationships, a motion plan for the medical device.