Digital Surgery Limited

Kinosis Ltd.

Other

Covidien LP

Ucl Business Plc

Danail Stoyanov

Andre Chow

Petros Giataganas

Imanol Luengo Muntion

Jean Nehme

James Kellerman

James Liu

Omar Alvi

Evangello Flouty

Neil Clancy

Odysseas Zisimopoulos

Mark Stacey

Sam Muscroft

George B Hanna

Shobhit Arya

Daniel S Elson

Geoffrey B Jones

Agostino Stilli

Dan Elson

Xiaofei Du

Piyamate Wisanuvej

Paul Riordan

The present disclosure relates to systems and methods that use computer-vision processing systems to improve patient safety during surgical procedures. Computer-vision processing systems may train machine-learning models using machine-learning techniques. The machine-learning techniques can be executed to train the machine-learning models to recognize, classify, and interpret objects within a live video feed. Certain embodiments of the present disclosure can control (or facilitate control of) surgical tools during surgical procedures using the trained machine-learning models.

Methods and systems for using computer-vision to enhance surgical tool control during surgeries

An aspect includes a computer-implemented method that de-identifies data received from microphones. The method includes receiving data from one or more microphones and de-identifying the data. The de-identifying includes inputting the data into a machine learning system that has been trained to detect patterns in the data that are likely to identify a specific entity, and to remove the detected patterns from the data to generate de-identified data. An output from the machine learning system is received, where the output includes the de-identified data. According to some aspects, the microphones can be located in an operating room.

De-identifying data obtained from microphones

The present disclosure relates to processing data streams from a surgical procedure using multiple interconnected data structures to generate and/or continuously update an electronic output. Each surgical data structure is used to determine a current node associated with a characteristic of a surgical procedure and present relevant metadata associated with the surgical procedure. Each surgical data structure includes at least one node interconnected to one or more nodes of another data structure. The interconnected nodes between one or more data structures includes relational metadata associated with the surgical procedure.

Methods and systems for using multiple data structures to process surgical data

In some embodiments, methods and systems are provided for accessing a surgical dataset including surgical data collected during performance of a surgical procedure. The surgical data can include video data of the surgical procedure. Using the surgical data, a plurality of procedural states associated with the surgical procedure can be determined. For a procedural state of the plurality of procedural states, temporal information can be identified that identifies a part of the video data to be associated with the procedural state. For the procedural state of the plurality of procedural states, electronic data can be generated that characterizes the part of the video data and outputting the electronic data associated with the plurality of procedural states.

Surgical tracking and procedural map analysis tool

An apparatus for capsule endoscopy, the apparatus comprising a capsule that comprises: at least one inflatable bladder configured to form a toroid having a hole and an outer periphery when inflated; a plurality of continuous tracks, each extending through the hole and around the outer periphery of the at least one inflatable bladder; and a propulsion system configured to drive the continuous tracks; wherein the capsule is configured such that the continuous tracks slip over the at least one inflatable bladder when driven by the propulsion system.

Apparatus and method for capsule endoscopy

A computer implemented method is provided for a virtual training system. A virtual surgical simulation associated with a type of surgical procedure is accessed. Image data associated with a controller and a workspace is received. Controller data corresponding to a controller interaction is received. A first interaction of the controller within the workspace based on at least one of the image data and the controller data is determined. Using the set of one or more transformation rules, the first interaction of the controller is transformed to a manipulation of a virtualized surgical tool in the virtual surgical simulation. A representation is output of the manipulation of the virtualized surgical tool.

Techniques for virtualized tool interaction

A method and apparatus are provided for estimating the value of a physical parameter of biological tissue. The method comprises acquiring a colour image of the biological tissue from a single image capture device; extracting from the colour image at least two images in respective optical wavebands having a different spectral sensitivity from one another, whereby a given location in the biological tissue is present in each of the extracted images; providing a physical model of the optical properties of the biological tissue, wherein the optical properties of the biological tissue are sensitive to the value of said physical parameter; and estimating the value of the physical parameter at said given location based on an intensity value at that location for each extracted image. The estimating utilises the physical model of the optical properties of the biological tissue and the spectral sensitivity for each respective waveband.

Method and apparatus for estimating the value of a physical parameter in a biological tissue

A medical instrument includes a housing and a shaft coupled to the housing. The shaft has a proximal end and a distal end. An end effector assembly is disposed at the distal end of the shaft. The end effector assembly includes first and second jaw members. At least one of the first and second jaw members is movable from a first position wherein the first and second jaw members are disposed in spaced relation relative to one another to at least a second position closer to one another wherein the first and second jaw members cooperate to grasp tissue therebetween. The medical instrument also includes one or more light-emitting elements and one or more light-detecting elements configured to generate one or more signals indicative of tissue reflectance. The one or more light-emitting elements are adapted to deliver light energy to tissue grasped between the first and second jaw members.

Surgical device with an end effector assembly and system for monitoring of tissue before and after a surgical procedure

A set of virtual images can be generated based on one or more real images and target rendering specifications, such that the set of virtual images correspond to (for example) different rendering specifications (or combinations thereof) than do the real images. An image style can be transferred to the at least some of the virtual images of the set of virtual images to generate a stylized virtual image. A machine-learning model can be trained using a plurality of stylized virtual images. Another real image can then be processed using the trained machine-learning model. The processing can include segmenting the other real image to detect whether and/or which objects are represented (and/or a state of the object). The object data can then be used to identify (for example) a state of a procedure.

State detection using machine-learning model trained on simulated image data

Growing community of inventors

London, United Kingdom

Danail Stoyanov