A method and system for detecting spinal stenosis is provided. The method may receive image data corresponding to a spine region of a patient. The method may also identify a spinal cord in the image data. The method may determine at least one compression of the spinal cord and may mark an anatomical element proximate to a location of the determined at least one compression to yield at least one marking. The method may generate a decompression plan based on the at least one marking.

A number of improvements are provided relating to computer aided surgery. The improvement relates to both the methods used during computer aided surgery and the devices used during such procedures. Some of the improvement relate to controlling the selection of which data to display during a procedure and/or how the data is displayed to aid the surgeon. Other improvements relate to the structure of the tools used during a procedure and how the tools can be controlled automatically to improve the efficiency of the procedure. Still other improvements relate to methods of providing feedback during a procedure to improve either the efficiency or quality, or both, for a procedure.

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.

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.

A robotic surgical system comprises a surgical tool, a manipulator configured to support the surgical tool, a force/torque sensor to measure forces and torques applied to the surgical tool, and a control system. The control system obtains a three-dimensional milling path for the surgical tool. The control system also receives one or more signals from the force/torque sensor in response to a user manually applying user forces and torques to the surgical tool. The control system determines a commanded pose to which to command the manipulator to advance the surgical tool along the milling path based on a tangential component of the user forces and torques, based on a virtual simulation using virtual constraints, and/or based on other suitable factors to promote guided, manual movement of the surgical tool along the milling path.

Logic may determine how to reduce bone segments. Logic may communicate one or more images to display with at least two bone segments. Logic may identify a first reduction point and a third point on a first bone segment and identify a second reduction point and a fourth point on the second bone segment. Logic may identify a fifth point on the first bone segment and a sixth point on the second bone segment. Logic may also divide the one or more images along a line or plane between the bone segments, bring the second reduction point and the associated image segment to the first reduction point, align the line or plane of the second bone segment with a line or plane of the first bone segment. Furthermore, logic may adjust alignment and record the movement of the image segments or compare original and final positions, to determine deformity parameters.

A spinal correction rod implant manufacturing process includes: estimating a targeted spinal correction rod implant shape based on a patient specific spine shape correction and including spine 3D modeling, one or more simulation loops each including: first simulating an intermediate spinal correction rod implant shape from modeling mechanical interaction between the patient specific spine and: either, for the first simulation, the implant shape, or, for subsequent simulation, if any, an overbent implant shape resulting from the previous simulation loop, a second simulation of an implant shape overbending applied to the targeted spinal correction rod implant shape producing an overbent spinal correction rod implant shape representing a difference between: either, for the first loop, the targeted spinal correction rod implant shape, or, for subsequent loop, if any, the overbent spinal correction rod implant shape resulting from the previous simulation loop, and the intermediate spinal correction rod implant shape.

Computer-implemented methods for modeling a surgical correction for a patient, and associated systems are disclosed herein. In some embodiments, the method includes obtaining patient data. The image data can depict a native anatomical configuration of a region of a patient's spine. The method also includes generating a virtual model of the patient's spine in the native anatomical configuration and/or a corrected anatomical configuration. The method can also include identifying one or more soft tissue surgical steps, predicting an effect of the soft tissue surgical steps, and generating a surgical plan for achieving the corrected anatomical configuration. The soft tissue surgical step can adjust an intraoperative mobility of vertebrae of the spine to achieve the corrected anatomical configuration. The surgical plan includes at least one of the soft tissue surgical steps to help facilitate movement of the vertebrae to the corrected anatomical configuration.

The disclosure relates to a path planning device for multi-probe joint cryoablation, the device comprising a memory and a processor. The memory stores a computer program, and the processor, when executing the computer program, implements the following steps: acquiring a target region in a medical scanned image of a target object and corresponding to a target tissue to be cryoablated;

selecting a single-probe ablation region from the target region; for the single-probe ablation region, obtaining a puncture path of single-probe cryoablation and a corresponding ice ball coverage region; and if the ice ball coverage region does not completely cover target region, then taking the remaining region of the target region from which the ice ball coverage region is excluded as a new target region, and returning to the step of selecting the selecting the single-probe ablation region from the target region.

Methods and systems of augmenting an implant intraoperatively and preparing a cone for revision surgical procedure are disclosed. A system includes a cutting device, a tracking and navigation system and a cutting system in operable communication with the cutting device and the tracking and navigation system. The cutting device includes a communication system, a cutting element, and a plurality of optical trackers. The tracking and navigation system is configured to detect a location of optical trackers. The control system is configured to cause the tracking and navigation system to detect the location of the cutting device, determine a revised shape for an implant cavity, cause the cutting device to cut the implant cavity to the revised shape, select a shape for a cone to be placed in the revised implant cavity, and machine the cone to the selected shape.