Abstract: A method and device is described for delivering radiation therapy beam arrangement and beam settings to a radiotherapy device treating a patient with a tumor based medical condition. Patient specific treatment parameters data for the medical condition are developed and modified by the system. The treatment parameters data includes at least radiotherapy beam arrangement or photon beam energy for treatment of the particularized patient tumor location. Patient specific treatment parameters data are derived from a selected treatment plan and may include outlining of the patient's tumor in the medical images, the relevant modified patient specific treatment parameters data transferred to a computer controlling the radiotherapy device to control and apply radiotherapy treatment to the patient according to the modified treatment data.

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: A computer-implemented medical method of irradiation treatment planning is provided. Therein, an initial coverage volume for a planning target volume, which is to be irradiated in an irradiation treatment with a prescribed dose, is provided. Further, at least one constraint indicative of an allowed dose for an organ at risk is provided. Applying an initial irradiation treatment plan, an organ dose deposited in at least a partial volume of the organ at risk is calculated. Based on comparing the organ dose to the at least one constraint, an amount of violation is determined. Taking into account the determined amount of violation, a reduction coverage volume is calculated for the planning target volume and a virtual planning object is generated based on changing a volume of the organ at risk, such that an overlap region of the virtual planning object and the planning target volume corresponds to the reduction coverage volume.

Abstract: Disclosed is a medical image data processing method for determining a clinical target volume for a medical treatment, wherein the method comprises executing, on at least one processor (3) of at least one computer (2), steps of: a) acquiring (S1) first image data describing at least one image of an anatomical structure of a patient; b) acquiring (S2) second image data describing an indicator for a preferred spreading direction or probability distribution of at least one target cell; c) determining (S3) registration data describing a registration of the first image data to the second image data by performing a co-registration between the first image data and the second image data using a registration algorithm; d) determining (S4) gross target region data describing a target region in the at least one image of the anatomical structure based on the first image data; e) determining (S5) margin region data describing a margin around the target region based on the gross target region data; f) determining (S6) clini

Abstract: The inventive approach positionally determines a periodically moving structure of a patient's anatomy by acquiring one or more images of a periodically moving anatomical structure of interest. The exposure time of each image covers at least one whole motion cycle of the structure, such that each acquired image depicts at least one whole motion cycle.

Abstract: Provided is a method for generating pose transformation data between first and second rigidly mounted digital cameras having non-coincident fields of view. The method includes obtaining a first plurality of images of a first calibration object, obtaining a second plurality of images of the first or a second calibration object, generating first and second object point data, generating first and second calibration data of the first and second digital cameras, determining first pose data between a first frame of reference of the first digital camera and the frame of reference of the first calibration object, determining second pose data between the frame of reference of the second digital camera and the frame of reference of the first or second calibration objects, and calculating the pose transformation data between the pose of the first digital camera and the pose of the second digital camera.

Abstract: A computer-implemented method for determining a target position of an X-ray device encompasses acquiring image data describing an anatomical structure of a patient, for example, by means of a 3D scan, and registering the image data relative to a coordinate system of the patient, for example by means of a navigation system. Furthermore, a trajectory of an implant positioned within the anatomical structure relative to the patient coordinate system is acquired. A target position of an X-ray device for acquiring an X-ray image of at least part of the implant is determined based on the registered image and the acquired trajectory of the implant.

Abstract: During a sEEG (stereo-electroencephalography) intervention into the skull of a patient, there is requirement to drill a large number of trajectories. Typically, instrument stabilisation platforms and robots for protocols requiring only one or two trajectories are rigidly fixed to the skull using surgical anchor members fixed into the skull around the one or two trajectories. However, because sEEG interventions require a large number of trajectories, an impractical number of surgical anchor members need to be fixed into the skull resulting in patient discomfort. Attachment of an intervention platform to all surgical anchor members is not required at once. Accordingly, it is proposed to search for intersection points of the maximum extent of an intervention platform between at least two trajectory entry points on an object of interest of patient, so that at least one surgical anchor member can be shared when the intersection point is at first and the second trajectories.

Abstract: The invention relates to a medical registration apparatus (1), comprising •two flanks (2a, 2b); •a pivot portion (3) around which at least one of the flanks (2a, 2b) is rotatable with respect to a rotation centre (3c, 3d) (FIG. 1, FIG. 3); •a contacting portion (4a, 4b) on each of the flanks (2a, 2b), each contacting portion (4a, 4b) being spaced apart from the rotation centre (3c, 3d); and •a sensor (5, 6) being arranged with an offset (r, FIG. 4 A) to a line (a) connecting the contacting portions (4a, 4b). The invention also relates to a data processing method for use with the medical registration apparatus.

Abstract: Disclosed is a computer-implemented method of determining one or more position and/or orientation parameters of an anatomical structure of a body portion. The anatomical structure has a longitudinal shape defining a longitudinal axis. The method includes generating and/or reading, by a data processing system, volumetric data of at least a portion of a subject. The method further includes generating and/or reading, by the data processing system, a deformable template which provides an estimate for a location of the longitudinal axis in the portion of the subject. The method further includes matching, by the data processing system, the deformable template to the volumetric data, thereby obtaining a matched template. The matching comprises using one or more internal energy functions and one or more external energy functions for optimizing an objective function.

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 hybrid phantom having marker patches that are visible both in a thermal image captured by a thermal camera and a 3D point cloud generated by a 3D camera. A thermal insulation between the marker, patches and a carrier part of the phantom maintains a temperature difference between the marker patches and the carrier part such that the marker patches are visible in the thermal image. Different optical properties of the marker patches and the carrier part make them distinguishable in the 3D point cloud.

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 patient's posture.