Abstract: A system for enhancing AI-based identifications of tools comprises memory and control circuitry. The memory is configured to store a first set of AI-based identifications of tools used during a medical procedure and supplemental data related to the medical procedure. The control circuitry is configured to group identifications of tools from the first set into timeblocks, the timeblocks including at least a first timeblock; determine that different tool identifications exist in the first timeblock, the different tool identifications including identifications for at least a first type of tool and a second type of tool; and based at least in part on the supplemental data, filter-out at least one of the first type of tool and the second type of tool from the first timeblock.

Abstract: A robotic system is configured to automatically identify surgical instruments used during a bronchoscopy procedure. The robotic system can include a video capture device, a robotic manipulator, sensors configured to detect a configuration of the robotic manipulator, and control circuitry communicatively coupled to the robotic manipulator. The control circuitry is configured to perform, using a machine learning classifier, a first analysis of a bronchoscopy video of a patient site to track a medical instrument in the bronchoscopy video. The control circuitry can then identify a set of possible instrument identifications for the medical instrument in the bronchoscopy video based on the first analysis and an identified phase of the bronchoscopy procedure. The control circuitry can then track a motion of the medical instrument in the bronchoscopy video and select an identification from the set of possible instrument identification for the medical instrument based at least on the tracked motion.

Abstract: The present disclosure relates to systems, devices, and methods to calibrate an endoscope with a location-sensor-to-camera transform or a camera-to-location-sensor transform.

Abstract: A robotic system is configured to automatically identify surgical instruments used during a bronchoscopy procedure. The robotic system can include a video capture device, a robotic manipulator, sensors configured to detect a configuration of the robotic manipulator, and control circuitry communicatively coupled to the robotic manipulator. The control circuitry is configured to perform, using a machine learning classifier, a first analysis of a bronchoscopy video of a patient site to track a medical instrument in the bronchoscopy video. The control circuitry can then identify a set of possible instrument identifications for the medical instrument in the bronchoscopy video based on the first analysis and an identified phase of the bronchoscopy procedure. The control circuitry can then track a motion of the medical instrument in the bronchoscopy video and select an identification from the set of possible instrument identification for the medical instrument based at least on the tracked motion.

Abstract: A method of localizing a target anatomy involves advancing a ureteroscope to a target calyx of a kidney of a patient through at least a portion of a urinary tract of the patient, determining a positional offset between one or more position sensors associated with the ureteroscope and a target papilla of the kidney that is at least partially exposed within the target calyx, and determining a percutaneous access target based at least in part on one or more of a present position of the one or more position sensors or the positional offset.

Abstract: Methods and systems provide improved navigation through tubular networks such as lung airways by providing improved estimation of location and orientation information of a medical instrument (e.g., an endoscope) within the tubular network. Various input data such as image data and CT data, are used to model the tubular networks, and the model information is used to generate a camera pose representing a specific site location within the tubular network and/or to determine navigation information including position and orientation for the medical instrument.

Abstract: Anatomical feature tracking involves advancing a medical instrument to a treatment site of a patient, the medical instrument comprising an imaging device, generating a first image of at least a portion of the treatment site using the imaging device of the medical instrument when a distal end of the medical instrument is in a first position, generating a first silhouette of a first target anatomical feature represented in the first image, generating a second image of at least a portion of the treatment site using the imaging device of the medical instrument when the distal end of the medical instrument is in a second position, generating a second silhouette of a second target anatomical feature represented in the second image, and determining a target position at the treatment site based at least in part on the first silhouette and the second silhouette.

Abstract: Co-manipulation robotic systems are described herein that may be used for assisting with surgical procedures, including laparoscopic surgery. The co-manipulation robotic systems allow a surgeon to use commercially-available surgical tools while providing benefits associated with surgical robotics. Advantageously, the surgical tools may be seamlessly coupled to the robot arms using a disposable coupler while the reusable portions of the robot arm remain in a sterile drape. Further, the co-manipulation robotic system may operate in multiple modes to enhance usability and safety, while allowing the surgeon to position the instrument directly with the instrument handle and further maintain the desired position of the instrument using the robot arm.

Abstract: A robotic system includes a robotic manipulator configured to manipulate an endoscope having a camera associated therewith and control circuitry configured communicatively coupled to the robotic manipulator. The control circuitry can be configured to receive an image depicting a field-of-view (FOV) of the camera associated with the instrument, detect an anatomical feature in the image, display a graphical interface that includes the image and a visual overlay indicating a location of the anatomical feature in the image, and track the anatomical feature based at least in part on determining that the anatomical feature is a target anatomical feature.

Abstract: A method of localizing a target anatomy involves advancing a ureteroscope to a target calyx of a kidney of a patient through at least a portion of a urinary tract of the patient, determining a positional offset between one or more position sensors associated with the ureteroscope and a target papilla of the kidney that is at least partially exposed within the target calyx, and determining a percutaneous access target based at least in part on one or more of a present position of the one or more position sensors or the positional offset.

Abstract: Anatomical feature tracking involves advancing a medical instrument to a treatment site of a patient, the medical instrument comprising an imaging device, generating a first image of at least a portion of the treatment site using the imaging device of the medical instrument when a distal end of the medical instrument is in a first position, generating a first silhouette of a first target anatomical feature represented in the first image, generating a second image of at least a portion of the treatment site using the imaging device of the medical instrument when the distal end of the medical instrument is in a second position, generating a second silhouette of a second target anatomical feature represented in the second image, and determining a target position at the treatment site based at least in part on the first silhouette and the second silhouette.

Abstract: A system for extracting information of objects from video captured during a medical procedure that includes an image repository configured to store image data representing views within a luminal network, a log repository configured to store commands and/or states associated with an object within the luminal network, and control circuitry. The control circuitry can be configured to generate change data representing changes of visual states of the object over a time period, access the log repository to determine logs including at least one command or at least one state associated with the object over the time period, and generate contextual information associated with the object based at least in part on (i) the change data and (ii) the at least one command or the at least one state associated with the object.

Abstract: Co-manipulation robotic systems are described herein that may be used for assisting with laparoscopic surgical procedures. The co-manipulation robotic systems allow a surgeon to use commercially-available surgical instruments while providing benefits associated with surgical robotics. Further, the co-manipulation robotic system may operate in multiple modes to enhance usability and safety, while allowing the surgeon to position the instrument directly with the instrument handle and further maintain the desired position of the instrument or a desired force applied by the instrument using the robot arm. For example, the robot arm may be moved automatically to maintain a constant tension force on an anatomical structure via the instrument in a constant tension mode.

Abstract: The present disclosure relates to systems, devices, and methods to reconstruct a three-dimensional model of an instrument and a procedure site using trained neural networks.

Abstract: The present disclosure relates to systems, devices, and methods to calibrate an endoscope with a location-sensor-to-camera transform or a camera-to-location-sensor transform.

Abstract: Methods and systems provide improved navigation through tubular networks such as lung airways by providing improved estimation of location and orientation information of a medical instrument (e.g., an endoscope) within the tubular network. Various input data such as image data and CT data, are used to model the tubular networks, and the model information is used to generate a camera pose representing a specific site location within the tubular network and/or to determine navigation information including position and orientation for the medical instrument.

Abstract: Methods and systems provide improved navigation through tubular networks such as lung airways by providing improved estimation of location and orientation information of a medical instrument (e.g., an endoscope) within the tubular network. Various input data such as image data and CT data, are used to model the tubular networks, and the model information is used to generate a camera pose representing a specific site location within the tubular network and/or to determine navigation information including position and orientation for the medical instrument.

Abstract: A system includes one or more processors configured to execute instructions to cause the system to access a plurality of images generated by one or more imaging devices of an endoscope when the endoscope is disposed within anatomy of a patient, for each of the plurality of images, determine a value for each of one or more image reliability metrics, and determine a position of the endoscope within the anatomy of the patient based at least in part on the one or more image reliability metrics of each of the plurality of images.

Abstract: Co-manipulation robotic systems are described herein that may be used for assisting with laparoscopic surgical procedures. The co-manipulation robotic systems allow a surgeon to use commercially-available surgical tools while providing benefits associated with surgical robotics. Advantageously, the surgical tools may be seamlessly coupled to the robot arms using a disposable coupler while the reusable portions of the robot arm remain in a sterile drape. Further, the co-manipulation robotic system may operate in multiple modes to enhance usability and safety, while allowing the surgeon to position the instrument directly with the instrument handle and further maintain the desired position of the instrument using the robot arm.

Abstract: A method of localizing a target anatomy involves advancing a ureteroscope to a target calyx of a kidney of a patient through at least a portion of a urinary tract of the patient, determining a positional offset between one or more position sensors associated with the ureteroscope and a target papilla of the kidney that is at least partially exposed within the target calyx, and determining a percutaneous access target based at least in part on one or more of a present position of the one or more position sensors or the positional offset.