A system and method for estimating a pose of an imaging device for one or more images is provided.

Detections in video frames of a video signal, which are output from a machine learning model, are associated to generate a detection chain. Display of a detection in the video signal is caused based on a position of the detection in the detection chain, the confidence value of the detection and the location of the detection.

A device includes an offset subtraction unit; an image sensor which receives, for each of a plurality of bright frames, a respective image signal obtained during a respective exposure time of the image sensor, and transmits the same to the offset subtraction unit, and receives, for a dark frame, a respective image signal obtained during a respective exposure time of the image sensor, and transmits the same to the offset subtraction unit; and a control unit which ensures that the image sensor alternately transmits a number of bright frames and one dark frame to the offset subtraction unit. An amount of light by which the respective image signal for each of the bright frames is generated is larger than an amount of light by which the respective image signal for the dark frame is generated; and the offset subtraction unit obtains an offset and subtracts the offset from a signal.

A processor device includes an image signal acquisition unit, a display control unit, and a region-of-interest detection mode image processing unit. The image signal acquisition unit acquires an image signal from an endoscope. The region-of-interest detection mode image processing unit detects a region-of-interest from the endoscopic image. The display control unit superimposes a highlight display of the region-of-interest on the endoscopic image and displays the endoscopic image on which the highlight display is superimposed. The processor device determines a visibility of the highlight display from image information of the endoscopic image and the highlight display, and notifies a user of a determination result.

An endoscope system sequentially acquires a plurality of endoscopic images by continuously imaging an observation target. A recognition processing unit detects, from the acquired endoscopic images, regions including a lesion portion as regions-of-interest. A recognition result correction unit corrects a position of the region-of-interest of the specific image by using a position of the region-of-interest of a previous image acquired before the specific image and a position of the region-of-interest of a subsequent image acquired after the specific image.

The image processing device 1X includes a detection model evaluation means 31X and a display control means 33X. The detection model evaluation means 31X is configured to perform an evaluation on suitability of a detection model for detecting an attention area to be noted based on a captured image Ic in which an inspection target is photographed by a photographing unit provided in an endoscope. The display control means 33X is configured to display candidate area information according to a display mode determined based on a result of the evaluation, the candidate area information indicating one or more candidate areas that are one or more candidates of the attention area, the candidate areas being detected by one or more detection models included in detection model(s) subjected to the evaluation, the candidate area information being superimposed on the captured image Ic which is displayed by a display device 2X.

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.

There is provided a filing device, a filing method, and a program that cause a still image and a motion image to be associated with each other, which are captured without being associated with each other. The problem is solved through a filing device including an acquisition unit that acquires at least one still image and at least one motion image, a still image analysis unit that analyzes a pixel value of the still image and extracts still image information, a motion image analysis unit that analyzes a pixel value of the motion image and extracts motion image information, and an associating unit that associates the still image with the motion image by comparing the still image information with the motion image information.

A method of generating a color image using a monochromatic image sensor. The method includes sequentially illuminating a surface in a plurality of colors, one color at a time. The monochromatic image sensor captures a plurality of image frames of the surface based on the plurality of colors. The plurality of image frames are identified, and at least one feature in the target of the plurality of image frames is highlighted. Color intensities of the plurality of image frames are normalized. A color intensity map of the target for each of the plurality of image frames is generated. A correlation score is determined by comparing each color intensity map of the plurality of image frames. The color image is generated based on the correlation score.

The usability in annotating an image of a subject derived from a living body is improved. An image analysis method is implemented by one or more computers and includes: displaying a first image that is an image of a subject derived from a living body; acquiring information regarding a first region based on a first annotation added to the first image by a user (S101); specifying a similar region similar to the first region from a region different from the first region in the first image, or a second image obtained by image capture of a region including at least a part of a region of the subject subjected to capture of the first image, based on the information regarding the first region (S102, S103); and displaying a second annotation in a second region corresponding to the similar region in the first image (S104).