A method includes, receiving multiple signals from multiple respective electrodes arranged along an inner circumference of a blood vessel that has been ablated. Based on the multiple signals, one or more quality measures of the ablated blood vessel are produced. A graphical presentation indicative of the one or more quality measures, is displayed to a user in a two-dimensional (2D) polar coordinate system.

Examples relate to apparatuses, methods and computer programs for controlling a microscope system, and to a corresponding microscope system. An apparatus for controlling a microscope system comprises an interface for communicating with a camera module. The camera module is suitable for providing camera image data of a head of a user of the microscope system. The apparatus comprises a processing module configured to obtain the camera image data from the camera module via the interface. The processing module is configured to process the camera image data to determine information on an angular orientation of the head of the user relative to a display of the microscope system. The processing module is configured to provide a control signal for a robotic adjustment system of the microscope system based on the information on the angular orientation of the head of the user.

A method includes generating an ablation programming language, which defines commands for (i) setting ablation protocol parameters and respective values, (ii) setting a configuration of an ablation system, (iii) applying automatic logic that relates the ablation protocol parameters and the values to the configuration of the ablation system, and (iv) generating one or more graphical user interfaces (GUIs) showing one or more of the parameters of the ablation protocol and the system configuration. The ablation programming language is provided for subsequent use with the ablation system.

A vessel harvesting system removes a target vessel from a patient for use as a bypass. An elongated harvesting instrument inserts into a body along a path of a target vessel which includes at least one side branch. The harvesting instrument includes a cutter for applying thermal energy to sever and cauterize the side branch. An endoscopic camera captures visible-light images from a distal tip of the instrument within a dissected tunnel around the target vessel. A thermal camera captures thermograms coinciding with the visible-light images to characterize a temperature present at respective surfaces in the tunnel. An image processor (e.g., an electronic controller) renders a video stream including the visible-light images and an overlay depicting the temperatures present on at least some of the respective surfaces when applying the thermal energy. A display presenting the video stream and overlay to a user can be an augmented-reality display.

Disclosed embodiments determine, at an early stage, suitability of an intraoperative image for further intraoperative surgical analysis. The determination of suitability may be made using a first angle (such as a first obturator angle) based on at least three pelvic feature points in a preoperative image, a corresponding second angle (such as a corresponding second obturator angle) based on at least three corresponding pelvic feature points in an intraoperative image, and by comparing the first angle and the corresponding second angle to determine intraoperative image suitability. The first intra-operative image is indicated as suitable for further intraoperative analysis when an absolute value of a difference between the first angle and the corresponding second angle does not exceed a threshold. When the intraoperative image is determined as unsuitable for further intraoperative analysis, an indication of a movement direction for a fluoroscopy camera used to capture the intraoperative image is provided.

A method includes, receiving: (i) a selected three-dimensional (3D) section that has been ablated in a patient organ in accordance with a specified contour, and (ii) a dataset, which is indicative of a set of lesions formed during ablation of the selected 3D section. The selected 3D section is transformed into a two-dimensional (2D) map, and checking, on the 2D map, whether the set of lesions covers the specified contour.

Provided are systems and methods for registration of location sensors. In one aspect, a system includes an instrument and a processor configured to provide a first set of commands to drive the instrument along a first branch of the luminal network, the first branch being outside a path to a target within a model. The processor is also configured to track a set of one or more registration parameters during the driving of the instrument along the first branch and determine that the set of registration parameters satisfy a registration criterion. The processor is further configured to determine a registration between a location sensor coordinate system and a model coordinate system based on location data received from a set of location sensors during the driving of the instrument along the first branch and a second branch.

A surgical stapling system for stapling the tissue of a patient is disclosed. The stapling system comprises a housing, a shaft extending from the housing, and an end effector extending from the shaft. The end effector comprises a plurality of staples removably stored therein and, also, an anvil configured to deform the staples. The stapling system further comprises a firing mechanism configured to deploy the staples along a staple firing path longer than 60 mm, a camera configured to capture an image of the patient tissue, a display, and a controller configured to generate an image of the staple firing path, wherein the images are displayed on the display.

Embodiments described herein provide various examples of a machine-learning-based visual-haptic system for constructing visual-haptic models for various interactions between surgical tools and tissues. In one aspect, a process for constructing a visual-haptic model is disclosed. This process can begin by receiving a set of training videos. The process then processes each training video in the set of training videos to extract one or more video segments that depict a target tool-tissue interaction from the training video, wherein the target tool-tissue interaction involves exerting a force by one or more surgical tools on a tissue. Next, for each video segment in the set of video segments, the process annotates each video image in the video segment with a set of force levels predefined for the target tool-tissue interaction. The process subsequently trains a machine-learning model using the annotated video images to obtain a trained machine-learning model for the target tool-tissue interaction.

Integrated table motion includes a device including a control unit and an arm having one or more joints and a distal portion. The control unit is configured to receive a table movement request from a separate table, determine whether to allow the table movement request based on one or more of whether a type of movement in the table movement request is permitted, whether one or more instruments mounted to the device are within a field of view of an imaging device, or whether one or more instruments mounted to the device are withdrawn into respective cannulas, allow the table to perform the table movement request based on the determining; track movement of the table while the table performs the table movement request; and maintain, using the joint(s) and based on the tracked movement of the table, a position and/or an orientation of the distal portion relative to the table.