Abstract: An endoscope apparatus includes a fiber optic cable with a proximal end and a distal end opposite the proximal end. The endoscope apparatus also includes a light source optically coupled to the proximal end of the fiber optic cable to emit visible light and excitation light into the fiber optic cable for output from the distal end. The light source is configured to emit both the visible light and the excitation light simultaneously, and a wavelength of the excitation light is outside a wavelength spectrum of the visible light. An image sensor coupled to the distal end of the fiber optic cable and positioned to receive a reflection of the visible light as reflected visible light.

Abstract: Systems and methods for acquiring images of a sample are provided. According to an aspect of the invention, a system includes a first light source that emits first light having a first wavelength as a temporally continuous beam; a second light source that emits second light having a second wavelength as a temporally modulated beam; and a scanning mirror that raster scans the first light across a sample during a raster scan period, and projects a structured light pattern of the second light onto the sample during the raster scan period. A first image of the sample is generated from at least a portion of the first light that is backscattered from the sample during the raster scan period, and a second image of the sample is generated from at least a portion of the second light that is backscattered from the sample during the raster scan period.

Abstract: An endoscope apparatus includes a fiber optic cable with a proximal end and a distal end opposite the proximal end. The endoscope apparatus also includes a light source optically coupled to the proximal end of the fiber optic cable to emit visible light and excitation light into the fiber optic cable for output from the distal end. The light source is configured to emit both the visible light and the excitation light simultaneously, and a wavelength of the excitation light is outside a wavelength spectrum of the visible light. An image sensor is configured to receive a reflection of the visible light as reflected visible light.

Abstract: A system for improving imaging during a surgical procedure includes an image sensor coupled to a controller. The image sensor is coupled to capture a video, including a first image frame with a smoke occlusion due to surgical smoke, of the surgical procedure. The first image frame includes a plurality of pixels each having an imaged color representing a view of the tissue affected by the smoke occlusion. The controller stores instructions that when executed causes the system to perform operations. The operations include determining an estimated true color of each of the plurality of pixels. The estimated true color is closer to an unoccluded color of the tissue than the imaged color. The operations also include generating, in response to determining the estimated true color, a desmoked first image frame with a reduced amount of the smoke occlusion relative to the first image frame.

Abstract: A system for robotic surgery includes a surgical robot with one or more arms, where at least some of the arms in the one or more arms holds a surgical instrument. An image sensor is coupled to capture a video of a surgery performed by the surgical robot, and a display is coupled to receive an annotated video of the surgery. A processing apparatus is coupled to the surgical robot, the image sensor, and the display. The processing apparatus includes logic that when executed by the processing apparatus causes the processing apparatus to perform operations including identifying anatomical features in the video using a machine learning algorithm, and generating the annotated video. The anatomical features from the video are accentuated in the annotated video. The processing apparatus also outputs the annotated video to the display in real time.

Abstract: Embodiments may include a method to estimate motion data based on test image data sets. The method may include receiving a training data set comprising a plurality of training data elements. Each element may include an image data set and a motion data set. The method may include training a machine learning model using the training data set, resulting in identifying one or more parameters of a function in the machine learning model based on correspondences between the image data sets and the motion data sets. The method may further include receiving a test image data set. The test image data set may include intensities of pixels in a deep-tissue image. The method may include using the trained machine learning model and the test image data set to generate output data for the test image data set. The output data may characterize motion represented in the test image data set.

Abstract: An endoscope apparatus includes a fiber optic cable with a proximal end and a distal end opposite the proximal end. The endoscope apparatus also includes a light source optically coupled to the proximal end of the fiber optic cable to emit visible light and excitation light into the fiber optic cable for output from the distal end. The light source is configured to emit both the visible light and the excitation light simultaneously, and a wavelength of the excitation light is outside a wavelength spectrum of the visible light. An image sensor coupled to the distal end of the fiber optic cable and positioned to receive a reflection of the visible light as reflected visible light.

Abstract: An apparatus, system and process for guiding a surgeon during a medical procedure to prevent surgical mistakes are described. The system may include a machine learning medical procedure server that generates one or more machine learning medical procedure models using, at least, medical procedure data captured during medical procedures performed at a plurality of different medical procedure systems. The system may also include a medical procedure system communicably coupled with the machine learning medical procedure server that receives a selected machine learning medical procedure model from the machine learning medical procedure server, and utilizes the selected machine learning medical procedure model during a corresponding medical procedure to control one or more operations of the medical procedure system.

Abstract: An imaging system (e.g., hyperspectral imaging system) receives an indication to compare a first object and a second object (e.g., two anatomical structures or organs in a medical environment). The imaging system accesses a classification vector for the first object and the second object, the classification vector having been extracted by separating a plurality of collected reflectance values for the first object from a plurality of collected reflectance values for the second object. A set of optimal illumination intensities for one or more spectral illumination sources of the imaging system is determined based on the extracted classification vector. The first and second objects are illuminated with the determined illumination intensities. A high-contrast image of the first and second objects is provided for display, such that the two objects can be readily distinguished in the image. The intensity of pixels in the image is determined by the illumination intensities.

Abstract: A method for simulating motion of cloth or other flexible membranes corrects surface-to-surface intersection involving a membrane. The method may be applied at time intervals of a conventional motion simulation for computer-generated animation. When a collision is detected, a function for a line of intersection between intersecting surfaces is parameterized in terms of vertices of the membrane model. The function is differentiated, and a correction factor is applied to the dynamic simulation in proportion to the value of the partial derivative for respected ones of the intersected vertices. The correction factor may be smoothed over a number of vertices in the vicinity of the intersected vertices.