Abstract: A processing device includes: a processor configured to: acquire a first distance which is a distance from a reference position on a movement path of an endoscope to a distal end of the endoscope that is moved along the movement path; perform reaching site recognition processing of acquiring an image captured by the endoscope and recognizing a site inside a subject, where the distal end of the endoscope has reached, based on the image; and derive a second distance, which is a distance of the distal end of the endoscope inserted into the subject from a specific site inside the subject, based on a result of the reaching site recognition processing and the first distance.

Abstract: A processor device includes an image signal acquiring unit, an image processing unit, and a display control unit. The image signal acquiring unit acquires a digital image signal corresponding to an observation mode from an endoscope. The image processing unit includes a region-of-interest-mode image processing unit. The display control unit performs switching control of switching between a first display method in which an endoscopic image is displayed in real time and a second display method in which a recognition result list is displayed.

Abstract: Provided are a medical image processing device, a medical image processing method, and an endoscope system that make it easy to compare a region of interest and its peripheral region with each other and make it unlikely to miss the region of interest if the region of interest in a time-series image is reported by using figures. A coordinates calculating unit (43) that calculates, on the basis of region-of-interest information indicating a region of interest in a time-series image, a plurality of sets of coordinates of interest on an outline of a polygon or circle having a symmetric shape that surrounds the region of interest. A reporting information display control unit (45B) that superposes figures on the basis of the calculated plurality of sets of coordinates of interest when superposing the figures for reporting the region of interest on the time-series image. Herein, the figures have a size that does not change with respect to a size of the region of interest.

Abstract: There are provided a machine learning system, a learning method, and a program that can facilitate learning of a large number of combined medical images. A machine learning system (10) includes: an image database (14) that stores a plurality of medical images; a geometric-shape database (16) that stores geometric shapes to be superimposed on the medical images; a processor (22); and a learning model (30), in which the processor (22) is configured to perform a selection accepting process of accepting selection of a medical image from among the medical images stored in the image database (14) and selection of a geometric shape from among the geometric shapes stored in the geometric-shape database (16), a geometric-shape combining process of combining the selected medical image and the selected geometric shape and generating a composite image, and a training process of making the learning model perform learning by using the composite image.

Abstract: A medical image processing apparatus includes a processor configured to acquire a medical image of a subject, perform image recognition on the medical image using a trained model, based on a result of the image recognition, in response to a region included in the medical image satisfying a determination criterion, identify the region included in the medical image as a captured region, and output information indicating that the region is the captured region with respect to a schematic diagram representing an organ.

Abstract: A processor generates a trained model by updating a learning model that uses an input image for training obtained by performing deterioration processing on a source image as input to output a first output image for training and a second output image for training, which have the number of pixels larger than the input image for training. A second intermediate layer of the learning model outputs a feature map to be input to a first output layer that outputs the first output image for training based on the feature map from a folded layer and a first intermediate layer. A third intermediate layer outputs the feature map to be input to a second output layer that outputs a second output image for training based on the feature map from the folded layer.

Abstract: An image acquisition unit sequentially acquires a medical image. A recognition processing unit applies a recognition process to the medical image. A recognition result display determination unit determines to display or not display the result of the recognition process on a display according to blur in the medical image. A display control unit controls the display of the recognition process according to the determination by the recognition result display determination unit.

Abstract: An image processing device includes a processor. The processor is configured to: recognize, based on a medical image in which an observation target region is shown, a position of the observation target region in the medical image; determine whether or not to perform output of a size of the observation target region based on the position; and measure the size based on the medical image in a case in which it is determined to perform the output.

Abstract: A medical support device includes a processor. The processor is configured to recognize, based on a medical image in which a plurality of observation target regions appear, positions of the plurality of observation target regions in the medical image, determine a priority of the plurality of observation target regions, based on the positions, measure sizes of the plurality of observation target regions, and output the sizes in accordance with the priority.

Abstract: In an endoscope apparatus including a processor, the processor specifies the position of a specific region and sets a reference scale in a picked-up image that is obtained from the image pickup of a subject on which the specific region formed by auxiliary measurement light is formed. Then, the processor extracts a region of interest, determines a measurement portion, calculates a measured value obtained from the measurement of the measurement portion, on the basis of the reference scale, and generates a measured value marker using the measured value. Further, the processor creates a specific image in which the measured value marker is superimposed on the picked-up image.

Abstract: A medical image processing apparatus includes a processor configured to perform: a first determination process of determining, based on an acquired medical image, whether any of a plurality of imaging target sites is included in the medical image; a second determination process of determining, if it is determined in the first determination process that any of the plurality of imaging target sites is included in the medical image, whether the medical image is an image satisfying a determination criterion of a site included in the medical image; and a display control process of displaying, if it is determined in the second determination process that the medical image is the image satisfying the determination criterion of the site included in the medical image, a notification indicator on a display unit, the notification indicator indicating that the image satisfying the determination criterion of the site included in the medical image is captured.

Abstract: A processing device includes: a processor configured to: acquire a distance from a reference position on a movement path of an endoscope to a distal end of the endoscope that is moved along the movement path; acquire, from a memory, target position information indicating a target position on the movement path; and perform control of giving a notification based on the distance and the target position information.

Abstract: There are provided a learning apparatus, a learning method, a program, a trained model, and an endoscope system that can perform efficient learning even when the learning is performed using pieces of data acquired under conditions different from each other. A learning apparatus includes a hierarchical network including a first input layer, a second input layer, a first intermediate layer, a first normalization layer, a second normalization layer, a second intermediate layer, and an output layer. A learning control unit of the learning apparatus causes first learning and second learning to be performed. In the first learning, a to-be-trained model is trained based on a first error between a first recognition result and a correct answer for first data. In the second learning, the to-be-trained model is trained based on a second error between a second recognition result and a correct answer for second data.

Abstract: A medical support device includes a processor. The processor is configured to detect a duodenal papilla region by executing image recognition processing on an intestinal wall image obtained by a camera provided in an endoscopic scope imaging an intestinal wall of a duodenum; display the intestinal wall image on a screen; and display an opening portion image simulating an opening portion existing in a duodenal papilla, in the duodenal papilla region in the intestinal wall image displayed on the screen.

Abstract: An endoscope system comprises an image acquisition unit, a discrimination processing unit, and a discrimination processing control unit. The image acquisition unit acquires an endoscope image obtained by imaging an observation target using an endoscope. The discrimination processing unit discriminates a portion having a specific feature in the observation target by performing discrimination processing, using an endoscope image. The discrimination processing control unit controls a start or an end of the discrimination processing on the basis of a change in operation of an endoscope or the endoscope image.

Abstract: Provided is a medical image processing apparatus, a medical image processing method, and a program that are capable of reducing a gap between recognition by a recognizer and recognition by a user. The medical image processing apparatus is a medical image processing apparatus including a processor (210), a memory (207), and a monitor (400). The processor (204) is configured to sequentially acquire a plurality of medical images in a chronological manner; recognize, on the basis of the acquired medical images, a specific scene in the medical images; acquire a recognition frequency of the recognized specific scene; and cause the monitor to display, in accordance with the recognition frequency, a notification indication that changes in two or more stages and that indicates a degree of recognition.

Abstract: An endoscope system comprises an image acquisition unit, a discrimination processing unit, and a discrimination processing control unit. The image acquisition unit acquires an endoscope image obtained by imaging an observation target using an endoscope. The discrimination processing unit discriminates a portion having a specific feature in the observation target by performing discrimination processing, using an endoscope image. The discrimination processing control unit controls a start or an end of the discrimination processing on the basis of a change in operation of an endoscope or the endoscope image.

Abstract: An image processing device includes a processor, in which the processor acquires a lumen direction that is a direction in which an endoscope is inserted, from an image obtained by imaging a tubular organ via a camera provided in the endoscope, in accordance with a trained model obtained through machine learning based on a positional relationship between a plurality of division regions obtained by dividing the image and a lumen corresponding region included in the image, and outputs lumen direction information that is information indicating the lumen direction.

Abstract: A medical image processing apparatus includes the following. A processor is configured to: acquire a medical image obtained by capturing an image of an observation target; detect a region of interest from the medical image; and cause a display to display report information and the medical image, the report information reporting that the region of interest has been detected. A screen displayed on the display has a first region in which the medical image is displayed, and a second region provided outside the first region. The second region is divided into four regions by using line segments passing through a center of the first region, and a detected location of the region of interest is reported by displaying the report information in one of the four regions.

Abstract: An image processing apparatus acquires a color image including a plurality of primary color signals, performs color space conversion processing on the color image to generate a brightness signal image and a color difference signal image, performs super-resolution processing on the brightness signal image and the color difference signal image to generate a prediction brightness signal image, and uses the prediction brightness signal image to generate a super-resolution color image in which a resolution of the color image is increased.