An in-situ fusion system includes at least one robotic arm; a bioprinter; a polymerization tool; at least one processor; and a memory storing instructions for execution by the at least one processor. The instructions, when executed, cause the at least one processor to: control the at least one robotic arm to prepare at least two bone surfaces to support cellular growth; cause the bioprinter to print, from a scaffold material, a scaffold between the at least two bone surfaces; and cause the polymerization tool to induce the scaffold material to polymerize.

Methods and devices are disclosed relating improved articular models, implant components, and related guide tools and procedures. In addition, methods and devices are disclosed relating articular models, implant components, and/or related guide tools and procedures that include one or more features derived from patient-data, for example, images of the patient's joint. The data can be used to create a model for analyzing a patient's joint and to devise and evaluate a course of corrective action. The data also can be used to create patient-adapted implant components and related tools and procedures.

At least one embodiment comprises a talus implant comprising: a body section; a neck section; a crown, wherein the crown is positioned at a top portion of the body section; at least one wing coupled to the body section, wherein the wing extends out from the body section. At least one embodiment further comprises at least one screw hole positioned in at least one of the neck section and the body section. In at least one embodiment the outer surface of the implant is polished. In at least one embodiment a portion of the outer surface is polished while a portion of the outer surface is roughened.

A method for utilizing robotic surgical data for providing surgical training is disclosed. The method includes collecting, by a computing device, data related to a surgical procedure from one or more components of a computer-assisted surgical system. At least one of the one or more components is a robotically controlled surgical device. A graphical depiction representative of the surgical procedure is generated based on the collected data from the one or more components of the computer-assisted surgical system and one or more images providing a visual depiction of a patient's anatomy. A graphical user interface is output to a display device. The graphical user interface includes the graphical depiction of the surgical procedure and the collected data from the one or more components of the computer-assisted surgical system, to provide surgical training.

A method for utilizing robotic surgical data for a long term episode of care is disclosed. The method includes collecting data related to a surgical episode of care for a patient comprising pre-operative data, intraoperative data, and post-operative data. The intraoperative data is collected from one or more components of a computer-assisted surgical system. At least one of the one or more components is a robotically controlled surgical device. An analysis of the data related to the surgical episode of care is performed to evaluate one or more aspects of the surgical episode of care. A graphical depiction representative of the one or more aspects of the surgical episode of care is generated based on the performed analysis. A graphical user interface is output to a display device, the graphical user interface comprising the graphical depiction of the one or more aspects of the surgical episode of care.

A method for creating a patient-specific surgical plan includes receiving one or more pre-operative images of a patient having one or more infirmities affecting one or more anatomical joints, three-dimensional anatomical model of the one or more anatomical joints is created based on the one or more pre-operative images. One or more transfer functions and the three-dimensional anatomical model are used to identify a patient-specific implantation geometry that corrects the one or more infirmities. The transfer functions model performance of the one or more anatomical joints as a function of anatomical geometry and anatomical implantation features, surgical plan comprising the patient-specific implantation geometry may then be displayed.

In various embodiments, an implant for interfacing with a bone structure includes a web structure including a space truss. The space truss includes two or more planar truss units having a plurality of struts joined at nodes and the web structure is configured to interface with human bone tissue. In some embodiments, a method is provided that includes accessing an intersomatic space and inserting an implant into the intersomatic space. The implant includes a web structure including a space truss. The space truss includes two or more planar truss units having a plurality of struts joined at nodes and the web structure is configured to interface with human bone tissue.

The present invention relates to a system for producing artificial osseous tissue comprising: a client computer acquiring an image information of a subject bone tissue from an imaging unit that picks up an image of a subject bone tissue of a patient to generate a 3D image information; a server computer identifying the subject bone tissue based on the image information of the subject bone tissue received from the client computer, generating a 3D image information of at least one therapeutic bone tissue model corresponding to the subject bone tissue, and transmitting the 3D image information of the at least one therapeutic bone tissue model to the client computer; and a machining unit for fabricating an artificial bone tissue based on the 3D image information of the therapeutic bone tissue model determined from the server computer.

A coated powder composite may include a core particle of Ca or an alloy thereof, or of Mg or an alloy thereof. One or more coating layers may be disposed about the core particle, cladding the core particle. The coated powder composite may be biodegradable.

Methods, non-transitory computer readable media, and surgical computing devices are illustrated that improve robotic surgical systems. With this technology, one or more machine learning models are trained based on historical state data obtained for a computer-assisted surgical system (CASS) at each of a plurality of time periods during a plurality of historical knee arthroplasty surgical procedures. One or more of the machine learning models are applied to initial state data for a current knee arthroplasty surgical procedure to generate robotic commands required to achieve one or more future states of the CASS. The initial state data comprises a surgical plan. One or more surgical tools of the CASS are then manipulated based on the robotic commands to achieve the one or more future states of the CASS and thereby carry out at least a portion of the surgical plan.