A method for adjusting the operation of a surgical instrument using machine learning in a surgical suite is disclosed. The method comprises the steps of gathering data during surgical procedures, wherein the surgical procedures include the use of a surgical instrument, analyzing the gathered data to determine an appropriate operational adjustment of the surgical instrument, and adjusting the operation of the surgical instrument to improve the operation of the surgical instrument.

A surgical system includes a robotic device, a surgical tool mounted on the robotic device, and a processing circuit. The processing circuit is configured to receive image data of an anatomy, generate a virtual bone model based on the image data, identify a soft tissue attachment point on the virtual bone model, plan placement of an implant based on the soft tissue attachment point, generate a control object based on the placement of the implant, and control the robotic device to confine the surgical tool within the control object.

Systems and methods for visualizing navigation of a medical device with respect to a target using a live fluoroscopic view. The methods include displaying, in a screen, a three-dimensional (3D) view of a 3D model of a target from the perspective of a medical device tip. The methods also include displaying, in the screen, a live two-dimensional (2D) fluoroscopic view showing a medical device, and displaying a target mark, which corresponds to the 3D model of the target, overlaid on the live 2D fluoroscopic view. The methods may include determining whether the medical device tip is aligned with the target, displaying the target mark in a first color if the medical device tip is aligned with the target, and displaying the target mark in second color different from the first color if the medical device tip is not aligned with the target.

Examples of systems and methods described herein may utilize augmented reality devices and pointers in generating intra-operative plans and providing guidance for knee surgery. A pointer may indicate one or more anatomical points. An augmented reality device may detect positions of knee anatomical features based on a position of the pointer and positions of fiducials associated with a marker affixed to body part proximate to a knee, such as a femur or a tibia. The augmented reality device may generate a planned resection plane based on the positions of the knee anatomical features, and determine an actual resection plane based on a view of a resection guide having a marker inserted in the guide. The augmented reality device may provide guidance to position the guide to align the actual resection plane with the planned resection plane.

Described herein are methods and systems for performing a procedure for ovarian rebalancing. The methods and systems may be used in the treatment of polycystic ovary syndrome (PCOS). The systems and methods may also be useful in the treatment of infertility associated with PCOS.

A surgical system includes an arm extending from the base and having a distal end configured to be coupled to a tool, a first marker coupled in fixed relation to the base, and a tracking system. The tracking system is configured to collect first data indicative of a position of the first marker and collect second data indicative of a position an anatomical feature of a patient. The surgical system also includes a processor configured to calculate a position of the tool relative to the anatomical feature based on the first data and the second data.

A computer assisted surgery system comprising: a computerised surgical apparatus; and a control apparatus; wherein the control apparatus comprises circuitry configured to: receive information indicating a first region of a surgical scene from which information is obtained by the computerised surgical apparatus to make a decision; receive information indicating a second region of the surgical scene from which information is obtained by a medical professional to make a decision; determine if there is a discrepancy between the first and second regions of the surgical scene; and if there is a discrepancy between the first and second regions of the surgical scene: perform a predetermined process based on the discrepancy.

A computer assisted surgery system comprising an image capture apparatus, a display, a user interface and circuitry, wherein the circuitry is configured to: receive information indicating a surgical scenario and a surgical process associated with the surgical scenario; obtain an artificial image of the surgical scenario; output the artificial image for display on the display; receive permission information via the user interface indicating if there is permission for the surgical process to be performed if the surgical scenario is determined to occur.

A robotic arm system for surgery is described. The method includes: processing circuitry configured to: apply a virtual barrier preventing a human controlled surgical device from entering an area within a surgical scene; and release the virtual barrier in response to a gesture.

A surgical robotic system includes: a surgical console having a display and a user input device configured to generate a user input and a surgical robotic arm having a surgical instrument configured to treat tissue and being actuatable in response to the user input; and a video camera configured to capture video data that is displayed on the display. The system also includes a control tower coupled to the surgical console and the surgical robotic arm. The control tower is configured to: process the user input to control the surgical instrument and to record the user input as input data; train a machine learning system using the input data and the video data; and execute the at least one machine learning system to determine probability of failure of the surgical instrument.