Abstract: An example method includes registering a virtual model of a portion of a bone of a patient with a corresponding observed portion of the bone, the virtual model including a representation of a wall of the bone; registering a virtual model of an implant component with a corresponding observed implant component; and indicating, based on the registered virtual model of the portion of the bone and the registered virtual model of the implant component, a position of at least a portion of the implant component relative to a position of the wall of the bone.

Abstract: An example method includes registering a virtual model of a portion of a bone of a patient with a corresponding observed portion of the bone, the virtual model including a representation of a wall of the bone; registering a virtual model of an implant component with a corresponding observed implant component; and indicating, based on the registered virtual model of the portion of the bone and the registered virtual model of the implant component, a position of at least a portion of the implant component relative to a position of the wall of the bone.

Abstract: A method for pre-morbid characterization of patient anatomy includes obtaining a first point cloud representing a morbid state of a bone of a patient, generating information indicative of at least one of pathological portions of the first point cloud or non-pathological portions of the first point cloud, the pathological portions of the first point cloud being portions corresponding to pathological portions of the morbid state of the bone, and the non-pathological portions of the first point cloud being portions corresponding to non-pathological portions of the morbid state of the bone, generating a second point cloud that includes points corresponding to the non-pathological portions, and does not include points corresponding to the pathological portions, generating, based on these second point cloud, a third point cloud representing a pre-morbid state of the bone, and outputting information indicative of the third point cloud representing the pre-morbid state of the bone.

Abstract: A method for surgical planning includes obtaining, by a. computing system, a. first point cloud representing a first portion of a bone or a first cloud representing at least a portion of a bone, applying, by the computing system, a point cloud neural network to generate a second point cloud based on the first point cloud, the second point cloud comprising at least one of points representing at least a second portion of the bone or points representing an axis along the bone, and generating, by the computing system, surgical planning information based on the second point cloud.

Abstract: A computing system may be configured to obtain the first point cloud representing one or more bones of a patient, process the first point cloud using one or more point cloud neural networks to generate an output point cloud, the output point cloud including labels indicating locations of one or more landmarks on the one or more bones of the patient, and output the output point cloud.

Abstract: A method for predicting a tool alignment, the method comprising: obtaining, by a computing system, a first point cloud representing one or more bones of a patient; applying, by the computing system, a point cloud neural network to generate a second point cloud based on the first point cloud, the second point cloud, comprising points indicating the tool alignment; and determining, by the computing system, the tool alignment based on the points indicating the tool alignment.

Abstract: An example method includes obtaining, by one or more processors, a target atlas of a particular patient on which an arthroplasty procedure is to be performed; selecting, by the one or more processors and based on a comparison of values of the target atlas and a plurality of reference atlases of other patients on which the arthroplasty procedure has been performed, at least one reference atlas of the plurality of reference atlases of the other patients; and determining, by the one or more processors and based on the selected at least one reference atlas, one or both of an implant size and an implant alignment for the particular patient.

Abstract: An example device includes a surgical item for use in a surgical procedure; and a light on or within the surgical item. In this example, the light is controllable by an external device so as to identify the surgical item for use in the surgical procedure.

Abstract: An example medical device system includes a plurality of surgical items; and a visualization device configured to present a mixed reality (MR) presentation to a user; and one or more processors configured to select a surgical item of the plurality of surgical items based on a surgical procedure and present, in the MR presentation, virtual information that identifies the selected surgical item among the plurality of surgical items, wherein the virtual information is presented on or adjacent a position of the selected surgical item visible via the visualization device.

Abstract: An example mixed reality (MR) system includes a first MR device configured to present first medical information and first real-world information to a first user via a first MR presentation; a second MR device configured to provide second medical information and second real-world information to a second user via a second MR presentation; and a third device configured to provide third information to a third user, wherein the third information is based at least in part on the first MR presentation or the second MR presentation.

Abstract: An extended reality (XR) visualization device worn by an orthopedic surgeon outputs a XR visualization for display. The XR visualization includes a set of one or more virtual checklist items. Each of the one or more virtual checklist items corresponds to an item in a checklist of steps of an orthopedic surgery. Additionally, the XR visualization device detects a command of the orthopedic surgeon to select a virtual checklist item in the set of virtual checklist items. In response to detecting the command, the XR visualization device updates the XR visualization to include additional information regarding a step of the orthopedic surgery corresponding to the selected virtual checklist item.

Abstract: A computing system obtains an information model specifying a first surgical plan for an orthopedic surgery to be performed on a patient. Additionally, the computing system modifies the first surgical plan during an intraoperative phase of the orthopedic surgery to generate a second surgical plan. During the intraoperative phase of the orthopedic surgery, a visualization device may present a visualization for display that is based on the second surgical plan.

Abstract: An example system includes a first device configured to display a first presentation to a first user, wherein the first presentation includes one or more virtual elements configured to assist the first user in an orthopedic surgical procedure; and a second device configured to display a second presentation to a second user, wherein the second user provides surgical assistance on the orthopedic surgical procedure. In this example, the second device is further configured to display content that informs the second user on one or more previously-executed steps of the orthopedic surgical procedure.

Abstract: The present invention relates to safety in a dynamic 3D healthcare environment. The invention in particular relates to a medical safety-system for dynamic 3D healthcare environments, a medical examination system with motorized equipment, an image acquisition arrangement, and a method for providing safe movements in dynamic 3D healthcare environments. In order to provide improved safety in dynamic 3D healthcare environments with a facilitated adaptability, a medical safety-system (10) for dynamic 3D healthcare environments is provided, comprising a detection system (12), a processing unit (14), and an interface unit (16). The detection system comprises at least one sensor arrangement (18) adapted to provide depth information of at least a part of an observed scene (22). The processing unit comprises a correlation unit (24) adapted to correlate the depth information. The processing unit comprises a generation unit (26) adapted to generate a 3D free space model (32).

Abstract: An example method includes displaying, via a visualization device and overlaid on a portion of an anatomy of a patient viewable via the visualization device, a virtual model of the portion of the anatomy obtained from a virtual surgical plan for an orthopedic joint repair surgical procedure to attach a prosthetic to the anatomy; and displaying, via the visualization device and overlaid on the portion of the anatomy, a virtual guide that guides at least one of preparation of the anatomy for attachment of the prosthetic or attachment of the prosthetic to the anatomy.

Abstract: A computing system obtains an information model specifying a first surgical plan for an orthopedic surgery to be performed on a patient. Additionally, the computing system modifies the first surgical plan during an intraoperative phase of the orthopedic surgery to generate a second surgical plan. During the intraoperative phase of the orthopedic surgery, a visualization device may present a visualization for display that is based on the second surgical plan.

Abstract: A computing system may generate an initial segmentation mask by applying a neural network to a 3D image of a set of objects. The initial segmentation mask associates voxels of the 3D image with individual objects of the set of objects. Additionally, the computing system generates a refined segmentation mask. As part of generating the refined segmentation mask, the computing system performs, for each respective object, a front propagation process for the respective object. The front propagation process for the respective object uses input voxel data to relabel, in the refined segmentation mask, voxels of the 3D image as being associated with the respective object. A stopping condition of a path evaluated by the front propagation process for the respective object occurs when the front propagation process evaluates a voxel identified in the initial segmentation mask as being associated with a different one of the objects from the respective object.

Abstract: An example method includes registering, via a visualization device, a virtual model of a portion of an anatomy of an ankle of a patient to a corresponding portion of the anatomy of the ankle viewable via the visualization device, the virtual model obtained from a virtual surgical plan for an ankle arthroplasty procedure to attach a prosthetic to the anatomy. The example method also comprises displaying, via the visualization device and overlaid on the portion of the anatomy, a virtual guide that guides at least one of preparation of the anatomy for attachment of the prosthetic or attachment of the prosthetic to the anatomy.

Abstract: An example method includes registering, via a visualization device, a virtual model of a portion of an anatomy of an ankle of a patient to a corresponding portion of the anatomy of the ankle viewable via the visualization device, the virtual model obtained from a virtual surgical plan for an ankle arthroplasty procedure to attach a prosthetic to the anatomy. The example method also comprises displaying, via the visualization device and overlaid on the portion of the anatomy, a virtual guide that guides at least one of preparation of the anatomy for attachment of the prosthetic or attachment of the prosthetic to the anatomy.

Abstract: The present invention relates to safety in a dynamic 3D healthcare environment. The invention in particular relates to a medical safety-system for dynamic 3D healthcare environments, a medical examination system with motorized equipment, an image acquisition arrangement, and a method for providing safe movements in dynamic 3D healthcare environments. In order to provide improved safety in dynamic 3D healthcare environments with a facilitated adaptability, a medical safety-system (10) for dynamic 3D healthcare environments is provided, comprising a detection system (12), a processing unit (14), and an interface unit (16). The detection system comprises at least one sensor arrangement (18) adapted to provide depth information of at least a part of an observed scene (22). The processing unit comprises a correlation unit (24) adapted to correlate the depth information. The processing unit comprises a generation unit (26) adapted to generate a 3D free space model (32).