A support device for an endoscope comprises a tubular member configured for removable attachment to an outer surface of the endoscope near, or at, its distal end and a plurality of projecting elements extending outward from the outer surface of the tubular member and circumferentially spaced from each other. The device includes an optically transparent cover coupled to the tubular member and configured for covering the distal end of the endoscope when the tubular member is attached to the outer surface of the endoscope. The projecting elements provide support for the endoscope, improve visualization and center the scope as it passes through a body lumen, such as the colon. In addition, the cover seals the distal end of the endoscope to protect the scope and its components from debris, fluid, pathogens and other biomatter.

An electronic endoscope processor includes a converting means for converting each piece of pixel data that is made up of n (n≥3) types of color components and constitutes a color image of a biological tissue in a body cavity into a piece of pixel data that is made up of m (m≥2) types of color components, m being smaller than n; an evaluation value calculating means for calculating, for each pixel of the color image, an evaluation value related to a target illness based on the converted pieces of pixel data that are made up of m types of color components; and a lesion index calculating means for calculating a lesion index for each of a plurality of types of lesions related to the target illness based on the evaluation values calculated for the pixels of the color image.

The image processing apparatus acquires a plurality of types of candidate images based on an endoscope image, performs control of displaying, on a display, a display image based on at least one type of candidate image, performs a first analysis process on one or the plurality of types of candidate images set in advance, selects at least one type of candidate image from the plurality of types of candidate images as an optimum image based on a first analysis process result obtained through the first analysis process, and obtains a second analysis process result by performing a second analysis process on the optimum image.

Provided is a capsule endoscope. The capsule endoscope includes: an imaging device configured to perform imaging on a digestive tract in vivo to generate an image; an artificial neural network configured to determine whether there is a lesion area in the image; and a transmitter configured to transmit the image based on a determination result of the artificial neural network.

At least one vascular tree supplying at least a part of the hollow organ in the computed tomography dataset is segmented, and a tree structure up to an order possible based on the blood vessel segmentation result is determined from a blood vessel segmentation result. Perfusion information for each edge in the tree structure is assigned as at least one of the computed tomography data assigned to the blood vessel segment or at least one value derived therefrom. Adjacent hollow organ segments of the hollow organ are defined based on supply by adjacent blood vessels in the tree structure, and the tree structure and the perfusion information are analyzed to determine hemodynamic information to assign to hollow organ segments. At least a part of the hemodynamic information in at least one of the computed tomography dataset or a visualization dataset derived therefrom is then visualized.

An electronic endoscope system includes a plotting unit which plots pixel correspondence points, which correspond to pixels that constitute a color image that has multiple color components, on a first color plane according to color components of the pixel correspondence points, the first color plane intersecting the origin of a predetermined color space; an axis setting unit which sets a predetermined reference axis in the first color plane; a transform unit which defines a second color plane that includes the reference axis, and subjecting the pixel correspondence points on the first color plane to projective transformation onto the second color plane; and an evaluation value calculating unit which calculates a prescribed evaluation value with respect to the color image based on the pixel correspondence points subjected to projective transformation onto the second color plane.

An electronic endoscope processor includes a converting means for converting each piece of pixel data that is made up of n (n≥3) types of color components and constitutes a color image of a biological tissue in a body cavity into a piece of pixel data that is made up of m (m≥2) types of color components, m being smaller than n; an evaluation value calculating means for calculating, for each pixel of the color image, an evaluation value related to a target illness based on the converted pieces of pixel data that are made up of m types of color components; and a lesion index calculating means for calculating a lesion index for each of a plurality of types of lesions related to the target illness based on the evaluation values calculated for the pixels of the color image.

An image processing device acquires an image obtained by irradiating an area of a living body with light having a wavelength of 955 [nm] to 2025 [nm]. The image processing device inputs the acquired image to a learned model or a statistical model generated in advance for detecting, from the image, a tumor present in the area, and determines whether or not a tumor is present at each point in the image.

A medical information processing system according to an embodiment includes processing circuitry. The processing circuitry is configured to acquire information on an examination target, identify a reference image corresponding to the examination target on the basis of the information on the examination target, generate an edited image generated by editing the reference image, and transmit order information to which the edited image has been attached.

A computer-implemented system is provided that receives a real-time video captured from a medical image device during a medical procedure. The real-time video may include a plurality of frames. The system may be adapted to detect an object of interest in the plurality of frames and apply one or more neural networks configured to identify a plurality of characteristics of the detected object of interest, such as classification, size, and/or location. In some embodiments, the system is adapted to identify, based on one or more of the plurality of characteristics, a medical guideline and present, in real-time on a display device during the medical procedure, information for the medical guideline.