There is provided a method, comprising: feeding 2D image(s) of an internal surface of a colon captured by an endoscopic camera, into a machine learning model, wherein the 2D image(s) excludes a depiction of an external measurement tool, wherein the machine learning model is trained on records, each including 2D images of the internal surface of the colon of a respective subject labelled with ground truth labels of respective bounding boxes enclosing respective polyps and at least one of an indication of size and a type of the respective polyp indicating likelihood of developing maligiancy, obtaining a bounding box for a polyp and at least one of an indication of size and type of the polyp, and generating instructions for presenting within the GUI, an overlay of the bounding box over the polyp and the at least one of the indication of size and type of the polyp.

An information processing apparatus (2000) detects an abnormal region (30) from a predetermined range (16) of a video frame (14). The information processing apparatus (2000) determines whether a predetermined condition is satisfied in a case where the abnormal region (30) is detected from the predetermined range (16) of a certain video frame (14) and the abnormal region (30) is not detected from the predetermined range (16) of a predetermined video frame (14) generated later than the video frame (14). In a case where the predetermined condition is not satisfied, the information processing apparatus (2000) performs a predetermined notification.

Provided are a capsule endoscope apparatus for supporting a lesion diagnosis and a lesion diagnosis supporting method using the same. The capsule endoscope apparatus for supporting lesion diagnosis includes an imaging unit configured to capture one or more images of an inside of a body, a control unit configured to detect a suspected lesion region in the images and perform a precision diagnosis procedure when a suspected lesion region corresponding to a value equal to or greater than a certain threshold is detected, an image processing unit configured to process the images in the precision diagnosis procedure, and a communication module configured to transmit and receive processed images to another capsule endoscope apparatus or a terminal by using a wireless communication method.

A first image acquisition unit acquires a first image that is captured by a sensor having a first pixel arrangement pattern and includes a first reproduction band in a frequency domain. A second image acquisition unit acquires a second image that is captured by a sensor having a second pixel arrangement pattern and includes a second reproduction band different from the first reproduction band in the frequency domain. A correction processing unit generates a first correction image by correction processing of at least reducing or deleting high-frequency components that are not included in the second reproduction band within the first reproduction band.

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 apparatus for measuring a scanning pattern of an optical scanning apparatus can easily reduce the effect of stray light and improve the measurement accuracy of the scanning pattern. An apparatus for measuring a scanning pattern of an optical scanning apparatus (100), which scans an object being illuminated with illumination light and generates a display image of the object being illuminated, includes a screen (11) scanned by the illumination light and an optical position detector (12) that detects the position of an irradiation spot of the illumination light on the screen (11). The apparatus for measuring a scanning pattern sequentially detects a position of the irradiation spot at predetermined time points with the optical position detector (12) during scanning of the screen (11) to measure the scanning pattern of the illumination light.

A system includes a surgical instrument configured to perform a laparoscopic surgical operation, a location sensor configured to identify a spatial relationship between an anatomical structure and the surgical instrument, and a processor configured to receive a graphical representation of a patient, determine proximity of the distal end portion of the surgical instrument with the anatomical structure of the patient based on the spatial relationship, and generate a warning based on the determination of proximity.

An imaging device includes a light separator that separates light into light bands, and imaging elements that each receives one of the light bands and generates a corresponding signal. Each of the imaging elements has a pixel size of at most 2.5 μm by 2.5 μm. A registration error among the imaging elements is equal to or less than a threshold determined according to the pixel size.

An endoscope apparatus includes a display section with a touch panel having a left image display region and a right image display region and a control section. The control section is configured to perform display control so as to change, upon receiving a drag operation instruction while the left image display region selected, a position of a cursor displayed in the left image display region and the right image display region by an amount of variation da, and change, upon receiving a drag operation instruction while the right image display region selected, the position of the cursor displayed in the left image display region and right image display region by an amount of variation db.

Disclosed is a computer-implemented method of overlaying a representation of a medical instrument over a two-dimensional medical image. It finds at least one feature point along a detection line which is defined relative to the medical instrument in the medical image, calculates a geometrical quantity based on this feature point and adds the geometrical quantity to the two-dimensional medical image.