Abstract: A computer implemented method for determining a two dimensional DRR referred to as dynamic DRR based on a 4D-CT, the 4D-CT describing a sequence of three dimensional medical computer tomographic images of an anatomical body part of a patient, the images being referred to as sequence CTs, the 4D-CT representing the anatomical body part at different points in time, the anatomical body part comprising at least one primary anatomical element and secondary anatomical elements, the computer implemented method comprising the following steps: acquiring the 4D-CT; acquiring a planning CT, the planning CT being a three dimensional image used for planning of a treatment of the patient, the planning CT being acquired based on at least one of the sequence CTs or independently from the 4D-CT, acquiring a three dimensional image, referred to as undynamic CT, from the 4D-CT, the undynamic CT comprising at least one first image element representing the at least one primary anatomical element and second image elements represen

Abstract: A sterility-preserving robotic frontend-system, including a flexible trajectory-guide including at least one force- and/or torque-transmitting coupling-member, a baffle-member separating a sterile section from a non-sterile section, and a sterility-sleeve attached to the baffle-member; an actuator unit having a sensor unit that senses at least one of a) whether a trajectory-guide is placed with respect to the actuator unit in a manner that allows engaging-members to accurately engage an actuator interface, and b) whether the engaging-members have accurately engaged the actuator-interface; and a retainer-receptacle adapted to temporarily accommodate the trajectory guide, and to restrain flexibility of the trajectory-guide while it is accommodated. A packaging-container having an inner sterile volume containing the retainer-receptacle and the trajectory-guide and a method of setting up such a sterility-preserving robotic frontend-system.

Abstract: A computer-implemented medical data processing method for controlling a geometric status of a mechatronic articulable arm. Current geometric status data is acquired describing a current geometric status of the mechatronic articulable arm defined by a set of current spatial relationship between connected elements of the mechatronic articulable arm. Changed geometric status data describing a changed geometric status of the mechatronic articulable arm defined by a set of changed spatial relationship between the connected elements is determined based on current device position data, the current geometric status data, changed device position data, and device definition data. Instruction data describing an instruction for changing the geometric status of the mechatronic articulable arm from the current geometric status to the changed geometric status is determined. The instruction describes changes from the current spatial relationship to the changed spatial relationship.

Abstract: The present invention involves positionally identifying several anatomical structures of interest of a patient's anatomy on images which have been acquired at different points of time. For each anatomical structure a separate image fusion transformation between these images is performed. For at least one of the image fusion transformations it is then determined whether this transformation is within a predetermined threshold, wherein for this determination, at least one further image fusion transformation of another anatomical structure is taken into account.

Abstract: The present invention relates to a head immobilization system for immobilizing a patient's head in a supine position of the patient, the system comprising: a support rail structure adapted to be coupled to a patient rest and extending at least on both lateral sides of the patient's head, a mask frame adapted to be coupled to at least one deformable upper mask sheet, wherein the mask frame is releasably connected to the support rail structure via a first interface section and a second interface section, with at least two pins protruding from the first interface section in a first direction, and at least two pin-receptions provided at the second interface section, wherein each one of the pin-receptions receives one of the pins, and a catch-mechanism for each pin-reception and each corresponding pin, which allows the pin to be pushed further into the pin-reception in the first direction, but which interlocks in case of an attempted withdrawal of the pin from the pin-reception in a second, opposite direction.

Abstract: First and second skeleton model data is determined based on first and second surface data of a patient. Each of the skeleton model data describes geometries of rigid anatomic structures of a patient at a different point in time. Skeleton difference data is determined describing differences between the geometries of the rigid anatomic structures. In a next step, movement instruction data is determined which describes movement to be performed by the rigid anatomic structures to minimize the differences, i.e. to correct the posture of the patient. The movement instruction data is for example determined based on anatomy constraint data which describes anatomical movement constraints for the rigid anatomic structures (e.g. range of motion of a joint). An instruction is displayed (e.g. using augmented reality), guiding the user how to move the rigid anatomic structures so as to correct the patients posture.

Abstract: The disclosed method encompasses moving an object such as a medical device or instrument to a desired spatial position based on tracking data provided by a tracking system. Once it is determined from the tracking data that the object has reached the desired spatial position, a projection image is generated, which is registered with the desired spatial position and shows the object. Based on the image data, it is possible to verify whether the object has actually reached the desired position, or whether the object's actual position deviates from the desired position due to errors or inaccuracies, allowing measures to be taken to compensate for these errors or inaccuracies.

Abstract: Provided is a medical imaging apparatus having an AR-visualization module operably coupled to a camera and to a position determination module, which is adapted to create an AR-image based on an image received from the camera and an AR-overlay positionally registered with the image, and which includes a display interface adapted to transmit the created AR-image to a medical display.

Abstract: Disclosed is a computer-implemented method for generating an anonymized medical image of an anatomical body part of a patient, a corresponding computer program, a program storage medium storing such a program and a computer for executing the program, as well as a medical system comprising an electronic data storage device and the aforementioned computer. The disclosed method encompasses establishing a mapping from a patient image onto an atlas, changing that mapping, and applying the inverse of the changed mapping to the atlas in order to transform image content from the atlas to the patient image in order to achieve a deformed and thereby anonymised appearance of the patient image.

Abstract: Disclosed is a computer-implemented method of determining control data for increasing the braking force exerted by a braking mechanism of a mechatronic articulable arm on at least one or all joints connecting the arm elements of the mechatronic articulable arm to a level of braking force which is higher than the level required for locking the joint or joints, respectively. The control data is determined in dependence on both the relative position between the mechatronic articulable arm and an anatomical body part of patient, and a locking state of the mechatronic articulable arm.

Abstract: A head-holder support for attaching a medical head-holder to a patient table is provided that has a rigid base body, an adjustable and lockable head-holder interface at the base body, which is adapted to adjustably couple the head-holder to the base body by providing at least three degrees of freedom for the spatial relative position between the head-holder and the base body, wherein the at least three degrees of freedom are lockable so as to establish a rigid coupling between the head-holder and the base body, and at least one robotic arm interface at the base body, which is adapted to provide a rigid coupling between a robotic arm and the base body.

Abstract: A method for determining the relative position between a first camera and a second camera used in a medical application, wherein the first camera captures a 2D image of a phantom, the second camera emits light onto the phantom and analyzes the reflected light, thus generating a 3D point cloud representing points on the surface of the phantom, and the phantom has a planar surface forming a background on which a plurality of 2D markers are formed, wherein one of the background and the 2D markers is reflective, thus reflecting light emitted by the second camera back to the second camera, and the other one is non-reflective, thus not reflecting light emitted by the second camera back to the second camera, the method involving that a) the first camera captures a 2D image of the phantom, b) the second camera generates a 3D point cloud representing the planar surface of the phantom, c) the 2D markers are identified in the 2D image, thus obtaining 2D marker data representing the locations of the 2D markers in the 2D

Abstract: The present application provides an initial, or first, packed arc setup to be compared with predefined arc setup constraints. These predefined arc setup constraints constrain at least one or more of the number of patient table angles per target volume, the number of times the gantry moves along one arc per table angle, the sum of gantry span per metastasis over all arcs, and the minimum table span. Based on the result of the comparison between the first packed arc setup with the predefined arc setup constraints, a second arc setup is automatically suggested. The automatically suggested second arc setup may then be compared with the first arc setup by calculating a score for both setups. Several iterations of such a method can be carried out based on the comparison between an arc setup and the following, subsequent arc setup in the iteration.

Abstract: Disclosed is a computer-implemented method for determining a position of an anatomical tracking structure in a tracking image usable for controlling a radiation treatment such as at least one of radiotherapy or radio surgery of a patient, a corresponding computer program, a non-transitory program storage medium storing such a program and a computer for executing the program, as well as a system for the position of an anatomical tracking structure in a tracking image usable for controlling a radiation treatment such as at least one of radiotherapy or radio surgery of a patient, a system comprising an electronic data storage device and the aforementioned computer.

Abstract: Disclosed is a medical data processing method for determining an indicator relating to an injury of an anatomical structure (1) of a patient, wherein the method comprises executing, on at least one processor (5) of at least one computer (3), steps of: a) acquiring (S1) acceleration data describing an energy of a set of one or more signals in dependence on both time and frequency, the set of signals acquired by measuring the acceleration of the anatomical structure (1) over time; b) acquiring (S2) analysis data describing an analysis rule for determining at least one of b1) an overall energy level of at least one signal of the set of signals, b2) a correlation between at least two signals of the set of signals in the frequency domain, the at least two signals respectively measured at at least two different respective regions of the anatomical structure (1), or b3) a relationship between energies given for at least two different frequency ranges of at least one signal of the set of signals; c) determining (S3)

Abstract: Disclosed is a computer-implemented method which encompasses comparing the requirements for radiation therapy imposed by a patient's individual condition to the capabilities and requirements of different types of treatment machines to determine a suitable radiation treatment strategy including an identification of the treatment machine which shall be used and a treatment plan. Furthermore, a treatment plan is generated by simulating the envisaged radiation treatment. The type of treatment machine associated with a predetermined value for the sum of weights for all fields assigned to that treatment machine is determined as the treatment machine for treating the patient, and corresponding information is output detailing the treatment specifics such as radiation treatment parameters specifically suited for the patient target region tumor thereby reducing radiation exposure, efficient use of the machine and appropriate gating and tracking modes.

Abstract: Disclosed is a computer-implemented method of determining a treatment plan, encompassing acquiring patient image data, acquiring target data describing targets, acquiring position data describing control points which define one or more arcs, and determining target projection data which describes outlines of the target in a beam's-eye view. Margin data is acquired. For the outlines, margins are applied to determine auxiliary outlines. Beam shaping device data is determined describing configurations of the collimator leaves so that irradiation of the auxiliary outlines is enabled. Based on these configurations, the irradiation amount is simulated for voxels of the patient image data. Constraints to be fulfilled by the treatment plan may be set. Configurations of blockings, arc-weights and margins are proposed. Only different combinations of these parameters are proposed while additional possible parameters are neglected. An optimization algorithm is used to minimize an objective function.

Abstract: Disclosed is a computer-implemented method of determining a correspondence between a region of interest as it appears in a first digital medical patient image and as it appears in a second digital medical image. The correspondence is determined by calculating the ratio of overlap of the region of interest with a data object defining an anatomical body part in the first image and the second image and determining whether the larger of the two ratios exceeds a threshold. If the threshold is exceeded, the method assumes that the appearances in the two images describe the same region of interest.