Abstract: A visualization system including a video processing apparatus (VPA) including a processor; and memory having processing instructions stored therein and executable by the processor, the processing instructions operable to, when executed by the processor: determine an amplification gain level applied by the image sensor; determine, based on the amplification gain level, a denoising level and a corresponding sharpening level; and process image data to denoise and sharpen an image corresponding to the image signals using the denosing level and the sharpening level.

Abstract: A method of enhancing the visibility of blood vessels in a colour image captured by an image capturing device of a medical device, including, for at least some of the pixels of the image, the steps of: (a) processing data obtained from a first colour channel together with data obtained from a second colour channel to determine a value of a first parameter indicative of the intensity in the red spectrum relative to the total intensity of said pixel; (b) using said value of said first parameter and a first value of a user parameter to alter said pixel, the first value of the user parameter being based on user input, and wherein the strength of the alteration is dependent on both the value of said first parameter and the first value of said user parameter.

Abstract: A training system for an endoscopic procedure, the training system including an endoscope having an image sensor configured to generate images; an image processing device including a housing and a processing circuit in the housing, the processing circuit including a processor and memory, the memory having graphical user interface (GUI) logic and a trained single-pass neural network model, the processor being configured to process the neural network model and the GUI logic to present a GUI; and a physical model including cavities corresponding to interconnected human cavities. The GUI is configured to receive a user input corresponding to a training mode or an exam mode. In the training mode the GUI is configured to present navigation feedback, and in the exam mode the GUI is configured to not present navigation feedback.

Abstract: An image processing device for estimating a landing zone of a medical device extendable from a tip of an endoscope, the endoscope including one or more sensors including an image capturing device, the image processing device including a processing unit operationally connectable to the one or more sensors of the endoscope. The processing unit is configured to: obtain a stream of images captured by the image capturing device of the endoscope; process first sensor data recorded by the one or more sensors to estimate the landing zone of the medical device; and provide the stream of images with a visual indication, indicating the estimated landing zone.

Abstract: Disclosed is an image processing device for estimating a position of an endoscope in a model of the human airways using a first machine learning data architecture trained to determine a set of anatomic reference positions, said image processing device comprising a processing unit operationally connectable to an image capturing device of the endoscope, wherein the processing unit is configured to obtain a stream of recorded images; continuously analyse the recorded images of the stream of recorded images using the first machine learning data architecture to determine if an anatomic reference position of a subset of anatomic reference positions, from the set of anatomic reference positions, has been reached; and where it is determined that the anatomic reference position has been reached, update the endoscope position based on the anatomic reference position, and an endoscope system comprising an endoscope and an image processing device, a display unit comprising an image processing device, and a computer progr

Abstract: An image processing device including a housing and a processing circuit in the housing, the processing circuit including a processor and memory, the memory including a neural network model and proximity suppression logic, the neural network model comprising a single-pass neural network model trained with training images corresponding to an endoscopic procedure and defining anatomic references observable in the training images, wherein the neural network model is configured to process images, to detect the anatomic references in the images, and to output a set of anatomic references including identifiers and confidence values representing the likelihoods that the anatomic reference identifiers are correct, and wherein the proximity suppression logic is configured to change the confidence values of the anatomic references in the set of anatomic references based on a prior position of the endoscope to identify an anatomic reference indicative of the current position of the endoscope.

Abstract: A visualization system including a video processing apparatus (VPA) including a processor; and memory having processing instructions stored therein and executable by the processor, the processing instructions operable to, when executed by the processor: determine an amplification gain level applied by the image sensor; determine, based on the amplification gain level, a denoising level and a corresponding sharpening level; and process image data to denoise and sharpen an image corresponding to the image signals using the denosing level and the sharpening level.

Abstract: A visualization system including a video processing apparatus (VPA) including a processor; and memory having processing instructions stored therein and executable by the processor, the processing instructions operable to, when executed by the processor: determine an amplification gain level applied by the image sensor; determine, based on the amplification gain level, a denoising level and a corresponding sharpening level; and process image data to denoise and sharpen an image corresponding to the image signals using the denosing level and the sharpening level.

Abstract: A method of enhancing the visibility of blood vessels in a colour image captured by an image capturing device of a medical device, including, for at least some of the pixels of the image, the steps of: (a) processing data obtained from a first colour channel together with data obtained from a second colour channel to determine a value of a first parameter indicative of the intensity in the red spectrum relative to the total intensity of said pixel; (b) using said value of said first parameter and a first value of a user parameter to alter said pixel, the first value of the user parameter being based on user input, and wherein the strength of the alteration is dependent on both the value of said first parameter and the first value of said user parameter.

Abstract: A method of enhancing the visibility of blood vessels in a colour image captured by an image capturing device of a medical device, the colour image having a plurality of colour channels and a plurality of pixels, the method including for at least some of said plurality of pixels the steps of: (a) processing data obtained from a first colour channel together with data obtained from a second colour channel to determine a value of a first parameter indicative of the intensity in the red spectrum relative to the total intensity of said pixel; and (b) using said value of said first parameter to alter said pixel, wherein said first parameter has at least three possible values, and wherein the strength of the alteration is dependent on the value of said first parameter.

Abstract: A visualization system including a video processing apparatus (VPA) including a processor; and memory having processing instructions stored therein and executable by the processor, the processing instructions operable to, when executed by the processor: determine an amplification gain level applied by the image sensor; determine, based on the amplification gain level, a denoising level and a corresponding sharpening level; and process image data to denoise and sharpen an image corresponding to the image signals using the denosing level and the sharpening level.

Abstract: Disclosed is a method of enhancing the visibility of blood vessels in a colour image captured by an image capturing device of a medical device. The colour image having a plurality of colour channels and a plurality of pixels. The method comprises for at least some of said plurality of pixels the steps of: (a) processing data obtained from a first colour channel together with data obtained from a second colour channel to determine a value of a first parameter indicative of the intensity in the red spectrum relative to the total intensity of said pixel; (b) using said value of said first parameter to alter said pixel, wherein said first parameter has at least three possible values, and wherein the strength of the alteration is dependent on the value of said first parameter.

Abstract: A method of enhancing the visibility of blood vessels in a colour image captured by an image capturing device of a medical device, including, for at least some of the pixels of the image, the steps of: (a) processing data obtained from a first colour channel together with data obtained from a second colour channel to determine a value of a first parameter indicative of the intensity in the red spectrum relative to the total intensity of said pixel; (b) using said value of said first parameter and a first value of a user parameter to alter said pixel, the first value of the user parameter being based on user input, and wherein the strength of the alteration is dependent on both the value of said first parameter and the first value of said user parameter.

Abstract: A method of enhancing the visibility of blood vessels in a colour image captured by an image capturing device of a medical device, including, for at least some of the pixels of the image, the steps of: (a) processing data obtained from a first colour channel together with data obtained from a second colour channel to determine a value of a first parameter indicative of the intensity in the red spectrum relative to the total intensity of said pixel; (b) using said value of said first parameter and a first value of a user parameter to alter said pixel, the first value of the user parameter being based on user input, and wherein the strength of the alteration is dependent on both the value of said first parameter and the first value of said user parameter.