公开(公告)号：US20210012489A1

公开(公告)日：2021-01-14

申请号：US16955549

申请日：2019-09-12

Applicant: Brainlab AG

Inventor： Johannes Manus

IPC: G06T7/00 ,  G06T7/50 ,  G16H30/20 ,  G06T7/60

Abstract: Disclosed is a computer-implemented method of determining a hypersurface image from a tomographic image data set describing a tomographic image of an anatomical body part. The method encompasses a locally depth-of-view-corrected reconstruction of a volumetric data set (pre-operative image data, like CT or MRI image data), in order to e.g. augment volumetric image data onto e.g. a microscope view, or in the head-up display of the microscope. For the depth correction, a surface model of the actual anatomical surface of the anatomical body part is used which encompasses a hypersurface reconstruction pf the volumetric data set. Thus, the correct information related to the tissue at the current visible surface is overlaid.

公开(公告)号：US20200375661A1

公开(公告)日：2020-12-03

申请号：US16760922

申请日：2017-12-07

Applicant: Brainlab AG

Inventor： Jochen VEIGEL ,  Ivana IVANOVSKA ,  Hagen KAISER ,  Pablo APONTE

IPC: A61B34/10 ,  G09B19/00 ,  G06T15/10

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.

公开(公告)号：US10776959B2

公开(公告)日：2020-09-15

申请号：US16075431

申请日：2016-02-16

Applicant: Brainlab AG

Inventor： Kajetan Berlinger ,  Birte Domnik ,  Elisa Garcia Corsico ,  Pascal Bertram

IPC: G06T7/38 ,  G06T11/00 ,  A61N5/10 ,  A61B6/00 ,  A61B6/12 ,  A61B6/03 ,  G16H50/50 ,  G06T7/20 ,  G06T7/00

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 representing the secondary anatomical elements; acquiring at least one trajectory, referred to as primary trajectory, based on the 4D-CT, the at least one primary trajectory describing a path of the at least one first image element as a function of time; acquiring trajectories of the second image elements, referred to as secondary trajectories, based on the 4D-CT; for the image elements of the undynamic CT, determining trajectory similarity values based on the at least one primary trajectory and the secondary trajectories, the trajectory similarity values respectively describing a measure of similarity between a respective one of the secondary trajectories and the at least one primary trajectory; determining the dynamic DRR by using the determined trajectory similarity values, and, in case the planning CT is acquired independently from the 4D-CT, further using a transformation referred to as planning transformation from the undynamic CT to the planning CT, at least a part of image values of image elements of the dynamic DRR being determined by using the trajectory similarity values.

公开(公告)号：US10765332B2

公开(公告)日：2020-09-08

申请号：US15569535

申请日：2015-04-29

Applicant: Brainlab AG

Inventor： Christian Harrer ,  Stephan Mittermeyer ,  Bálint Varkuti

IPC: A61B5/00 ,  A61B5/024 ,  A61B5/0452 ,  A61B5/0245

Abstract: The invention relates to a computer-implemented medical data processing method for determining a heartbeat signal describing the heartbeat of a patient in the time domain, the method comprising executing, on a processor of a computer, steps of: a) acquiring, at the processor, acceleration measurement data describing an acceleration in the time domain of an anatomical body part measured on an external surface of the anatomical body part; b) determining, by the processor, component analysis data describing a result of an independent component analysis in the time domain of the acceleration measurement data; c) acquiring, at the processor, heartbeat template data describing template shapes of heartbeat in the time domain; d) determining, by the processor and based on the component analysis data and the heartbeat template data, recurrent shape data describing a recurrence of certain signal shapes in the component analysis data; e) determining, based on the recurrent shape data, heartbeat signal data describing a time series of the heartbeat.

公开(公告)号：US20200273199A1

公开(公告)日：2020-08-27

申请号：US16094002

申请日：2017-09-06

Applicant: Brainlab AG

Inventor： Daniel ROHDE

IPC: G06T7/73

Abstract: A hybrid phantom including a planar surface that includes a background surface having one of a first property and a second property, and a plurality of marker surfaces. Each marker surface of the plurality of marker surfaces having the other one of the first property and the second property. The first property involves having a high thermal emissivity of 0.8 or higher and the second property involves having a low thermal emissivity of 0.2 or less. One of the first property and the second property further involves being diffuse reflective and the other one of the first property and the second property further involves being specular reflective. A method using a system comprising the hybrid phantom, a first, thermal camera, a second, three-dimensional (3D) camera, and a computer.

公开(公告)号：US10750980B2

公开(公告)日：2020-08-25

申请号：US15528043

申请日：2014-12-02

Applicant: Brainlab AG

Inventor： Hagen Kaiser ,  Stephen Froehlich ,  Stefan Vilsmeier

IPC: A61B5/11 ,  H04N13/204 ,  A61B5/00 ,  A61B5/01 ,  G06T7/33 ,  G06T7/70 ,  G06T7/00 ,  A61B5/113 ,  A61N5/10 ,  G01J5/00 ,  G03B35/02 ,  A61B5/055 ,  A61B6/03 ,  A61B6/00 ,  H04N13/00 ,  H04N13/239 ,  G01J5/10 ,  G01R33/48

Abstract: A medical image processing method performed by a computer, for measuring the spatial location of a point on the surface of a patient's body including: acquiring at least two two-dimensional image datasets, wherein each two-dimensional image dataset represents a two-dimensional image of at least a part of the surface which comprises the point, and wherein the two-dimensional images are taken from different and known viewing directions; determining the pixels in the two-dimensional image datasets which show the point on the surface of the body; and calculating the spatial location of the point from the locations of the determined pixels in the two-dimensional image datasets and the viewing directions of the two-dimensional images; wherein the two-dimensional images are thermographic images.

公开(公告)号：US10603120B2

公开(公告)日：2020-03-31

申请号：US15566096

申请日：2016-09-13

Applicant: Brainlab AG

Inventor： Wolfgang Steinle ,  Christian Rabus ,  Nils Frielinghaus

IPC: A61B34/00 ,  A61B34/20 ,  A61B34/30 ,  A61B34/10 ,  A61B90/00 ,  G16Z99/00 ,  G06F19/00

Abstract: Disclosed is a medical data processing method for determining control data for an automated movement of a robotic system (1) to move a tool operatively associated with the robotic system (1), wherein the method comprises executing, on at least one processor of at least one computer (4), steps of: a) acquiring (S1) image data describing an image of an anatomical structure of a patient; b) determining (S2) planned position data, based on the image data, describing at least one planned position of the tool relative to the anatomical structure of the patient; c) acquiring (S3) status change data describing the change of data a status of the robotic system (1) from a first status to a second status, wherein in the first status a manual movement of at least one part of the robotic system (1) is allowed and in the second status a manual movement of the at least one part of the robotic system is inhibited; d) acquiring (S4) actual position data describing the actual position of an element of the statue change data robotic system, in particular the tool, relative to the anatomical structure; e) determining (S5), based on the planned position data and the status change data and the actual position data, control data describing instructions for controlling, in the second status of the robotic system (1), at least one actuator to move the tool.

公开(公告)号：US20200078133A1

公开(公告)日：2020-03-12

申请号：US16604673

申请日：2017-05-09

Applicant: Brainlab AG

Inventor： Sven Flossmann ,  Sebastian Stopp

IPC: A61B90/00 ,  A61B34/20 ,  G06T7/20 ,  G06T7/70 ,  G06T3/20 ,  G06T3/60 ,  G06T19/00

Abstract: This document relates to a medical application of augmented reality in which areal image shows a medical device, or at least a part thereof. In an exemplary application, the real image further shows at least a part of a patient's body which is (to be) treated using the medical device. A part of the medical device might not be visible in the real image, for example because it extends into or behind the patient's body. In this case, the virtual image can comprise an augmentation of the medical device, which, for example, represents at least the part of the medical device which is invisible in the real image. This document in particular addresses a correct alignment of the augmentation with the medical device

公开(公告)号：US20200069972A1

公开(公告)日：2020-03-05

申请号：US16328653

申请日：2018-03-02

Applicant: Brainlab AG

Inventor： Stefan Schell ,  Claus Promberger

IPC: A61N5/10

Abstract: A computer-implemented medical method of irradiation treatment planning is provided. Therein, an initial coverage volume (118) for a planning target volume (116), which is to be irradiated in an irradiation treatment with a prescribed dose, is provided. Further, at least one constraint (106, 110) indicative of an allowed dose for an organ at risk (120) is provided. Applying an initial irradiation treatment plan, an organ dose deposited in at least a partial volume of the organ at risk (120) is calculated. Based on comparing the organ dose to the at least one constraint (106, 110), 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 (116) and a virtual planning object (122) is generated based on changing a volume of the organ at risk (120), such that an overlap region (124) of the virtual planning object (122) and the planning target volume (116) corresponds to the reduction coverage volume. By removing at least a part of the overlap region (124) from the planning target volume (116), an optimized planning target volume (132) is generated.

公开(公告)号：US10561345B2

公开(公告)日：2020-02-18

申请号：US15767336

申请日：2015-12-11

Applicant: Brainlab AG

Inventor： Christian Brack ,  Mario Schubert

IPC: A61B5/00 ,  A61B5/107 ,  A61B5/11 ,  G06T7/00

Abstract: A computer implemented method for determining a center of rotation of a bone, comprising the steps of: a) acquiring image data representing a plurality of images taken by a camera while the bone is being rotated about the center of rotation, wherein the images show a marker device attached to the bone; b) forming a plurality of image pairs from the image data, wherein each image pair comprises two different images; c) determining a first relative position of the marker device relative to the camera from a first image of an image pair; d) determining a second relative position of the marker device relative to the camera from a second image of the same image pair; e) calculating a transformation of the first relative position into the second relative position; f) repeating steps c) to e) for all image pairs to obtain a plurality of transformations; and calculating the location of the center of rotation of the bone relative to the marker device from the plurality of transformations.