Artificial intelligence guidance system for robotic surgery
AssigneeNavLAB, Inc.
InventorsJeffrey Roh, Justin Esterberg
Life of this patent
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Abstract
This invention is a system and method for utilizing artificial intelligence to operate a surgical robot (e.g., to perform a laminectomy), including a surgical robot, an artificial intelligence guidance system, an image recognition system, an image recognition database, and a database of past procedures with sensor data, electronic medical records, and imaging data. The image recognition system may identify the tissue type present in the patient and if it is the desired tissue type, the AI guidance system may remove a layer of that tissue with the end effector on the surgical robot, and have the surgeon define the tissue type if the image recognition system identified the tissue as anything other than the desired tissue type.
Claims21
A method implemented in a computing system for at least partially controlling a robotic surgical apparatus to perform surgical actions, the method comprising:
- obtaining a first image of a region of interest associated with a subject;
- identifying a type of tissue shown in the first image based, at least in part, on a neural network model trained on an image training set;
- in response to determining that the identified type of tissue belongs to a set of targeted types, causing the robotic surgical apparatus to perform a first surgical action with respect to the region of interest in accordance with a surgical plan;
- obtaining a second image of the region of interest after completion of the first surgical action;
- and
- in response to a failure to identify a type of tissue shown in the second image based, at least in part, on the neural network model:
- presenting the second image to a user;
- and
- receiving an input from the user indicating a type of tissue shown in the second image.
A non-transitory computer-readable storage medium storing content that, when executed by one or more processors, causes the one or more processors to perform actions including:
- obtaining a first image of a region of interest associated with a surgery subject;
- identifying a type of tissue shown in the first image based, at least in part, on a neural network model;
- in response to determining that the identified type of tissue belongs to a set of targeted types, causing a robotic surgical apparatus to perform a first surgical action with respect to the region of interest in accordance with a surgical plan;
- and
- obtaining a second image of the region of interest after completion of the first surgical action;
- in response to a failure to identify a type of tissue shown in the second image based, at least in part, on the neural network model:
- presenting the second image to a user;
- and
- receiving an input from the user indicating a type of tissue shown in the second image.
A system for at least partially controlling a robotic surgical apparatus, comprising:
- one or more processors;
- at least one display;
- and
- memory storing contents that, when executed by the one or more processors, cause the system to perform actions including:
- obtaining one or more first images of a region of interest associated with a surgery subject;
- identifying one or more types of tissue shown in the one or more first images based, at least in part, on a neural network model;
- displaying the identified one or more types of tissue via a graphical user interface (GUI) on the at least one display;
- receiving one or more interactions with the GUI from a user that indicate one or more surgical configurations;
- causing a robotic surgical apparatus to perform one or more surgical actions with respect to the region of interest based, at least in part, on the one or more surgical configurations;
- obtaining one or more second images of the region of interest after completion of at least one of the surgical actions;
- and
- in response to a failure to identify one or more types of tissue shown in the one or more second images based, at least in part, on the neural network model:
- presenting at least one of the second images to the user;
- and
- receiving an input from the user indicating one or more types of tissue shown in the at least one of the second images.
Dependencies are inferred from the claim text.