Abstract: Devices and methods for determining a position of a hole drilled in tissue in endoscopic surgical procedures include a drill guide configured to guide a drill bit to drill a hole in tissue of internal anatomy of a patient, the drill guide comprising: a shaft configured to receive the drill bit, wherein a distal end of the shaft is configured to interface with the tissue; and at least one fiducial marker positioned proximate the distal end of the shaft and configured to provide position information for the hole in an endoscopic image captured by an endoscopic imaging device.

Abstract: Presented herein are systems and methods for performing three-dimensional measurements of a surgical space using two-dimensional endoscopic images. According to an aspect, video data taken from an endoscopic imaging device can be used to generate a three-dimensional model of the surgical space represented by the video data. In one or more examples, two-dimensional images from the video data can be used to generate a three-dimensional model of the surgical space. In one or more examples, the one or more two-dimensional images of the surgical space can include a fiducial marker as part of the image. Using both the depth information and a size reference provided by the fiducial marker, the systems and methods herein can generate a three-dimensional model of the surgical space. The generated three-dimensional model can then be used to perform a variety of three-dimensional measurements in a surgical cavity in an accurate and efficient manner.

Abstract: A tool for use in endoscopic surgical procedures includes a shaft, wherein the shaft includes a first end, a second end, and a first axis; and a pointer at the first end of the shaft, wherein the pointer includes: a tip located on the first end of the pointer, and a plurality of fiducial markers disposed on the pointer, wherein at least one of the fiducial markers is disposed on a surface that extends transversely to the first axis, wherein the plurality of fiducial markers are configured for providing information for locating the tip of the pointer in an endoscopic image captured by an endoscopic imaging device.

Abstract: A method for training a machine learning model to detect substances that compromise medical imaging clarity includes receiving imaging of tissue associated with a medical procedure type; receiving imaging of one or more substances that can affect clarity of imaging associated with the medical procedure type; combining at least a portion of the imaging of the tissue and at least a portion of the imaging of the one or more substances to generate machine learning training image data in which at least a portion of the tissue is at least partially obscured by the one or more substances; and training, with the training image data, a machine learning model to detect the one or more substances in imaging generated during a medical procedure of the medical procedure type.

Abstract: A method for determining an attribute associated with anatomy of interest of a patient includes receiving first image data capturing the anatomy of interest of the patient and at least one obstruction obscuring at least a portion of the anatomy of interest of the patient; generating, using at least one machine learning model, second image data in which at least a portion of the obstruction is replaced; and determining at least one attribute associated with the anatomy of interest based on the second image data.

Abstract: Presented herein are systems and methods for performing three-dimensional measurements of a surgical space using two-dimensional endoscopic images. According to an aspect, video data taken from an endoscopic imaging device can be used to generate a three-dimensional model of the surgical space represented by the video data. In one or more examples, two-dimensional images from the video data can be used to generate a three-dimensional model of the surgical space. In one or more examples, the one or more two-dimensional images of the surgical space can include a fiducial marker as part of the image. Using both the depth information and a size reference provided by the fiducial marker, the systems and methods herein can generate a three-dimensional model of the surgical space. The generated three-dimensional model can then be used to perform a variety of three-dimensional measurements in a surgical cavity in an accurate and efficient manner.

Abstract: According to an aspect, video data taken from an endoscopic imaging device can be used to automatically control a surgical pump for purposes of regulating fluid pressure in an internal area of a patient during an endoscopic procedure. Control of the pump can be based in part on one or more features extracted from video data received from an endoscopic imaging device. The features can be extracted from the video data using a combination of machine learning classifiers and other processes configured to determine the presence of various conditions within the images of the internal area of the patient. Using the one or more extracted features, the system can adjust the inflow and outflow settings of the surgical pump to regulate the fluid pressure of the internal area of the patient commensurate with the needs of the surgery and the patient at any given moment in time during the surgical procedure.

Abstract: A method for automatically generating and applying annotations to one or more images captured during a surgical procedure using an imaging tool are provided. In one or more examples, the annotations can be generated by applying one or more machine learning classifiers to the images to determine the presence of various features contained within the images. Optionally, the machine learning classifiers can be configured to determine the anatomy displayed in a particular image as well as the procedure step shown in a given image. Using these two determinations, the systems and methods described herein can generate one or more annotations that are then overlaid on or laid next to an image so as to provide the patient or other person viewing the image with context as to what the image is showing.