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: 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: 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 medical image processing apparatus includes a recognition unit that detects a region of interest from an acquired medical image and classifies the region of interest; a display control unit that causes emphasis display for emphasizing the region of interest and a classification for the region of interest to be displayed in a screen identical to a screen for displaying an observation target included in the medical image; and an observation image switching unit that switches whether to display consecutive images or to display a still image by using a display device. In a case where consecutive image display of an observation image is switched to still image display by the observation image switching unit, the display control unit makes a change for reducing visual recognizability of at least any of the emphasis display or the classification compared with a case of the consecutive image display of the observation image.

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.

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: 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: A medical image processing apparatus (14) is a medical image processing apparatus including a processor and an audio notifier (17) configured to output a notification sound. The processor is configured to perform: image reception processing for receiving time-series continuous images; region-of-interest detection processing for detecting a region of interest from the images; and audio control processing for performing control to cause the audio notifier to output the notification sound for a certain period if the region of interest is currently detected in the region-of-interest detection processing, the audio control processing causing the audio notifier to output the notification sound in accordance with a first time, the first time being a time from a time point at which detection of the region of interest has previously ended in the region-of-interest detection processing until a time point at which the region of interest is currently detected in the region-of-interest detection processing.

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: Provided are a medical image processing apparatus, a medical image processing method, and a program by which a user can efficiently observe a medical image. A processor of the medical image processing apparatus is configured to perform: medical image acquisition processing of sequentially acquiring time-series medical images; first scene recognition processing of recognizing at least one first scene from one medical image of the medical images; second scene recognition processing of recognizing a second scene from the one medical image if the at least one first scene is recognized; first notification processing of providing a notification indicating that the at least one first scene is recognized; and second notification processing of providing a notification indicating that the second scene is recognized.

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 are a training data collection apparatus, a training data collection method, and a program that easily collect training data for use in training of a model that discriminates a lesion from an endoscopic image, a training system, a trained model, and an endoscopic image processing apparatus. Endoscopic images are associated with respective pieces of findings-diagnosis information. When the endoscopic images and the respective piece of findings-diagnosis information that are associated with each other are recorded in a recording apparatus as training data for use in training of a model that discriminates a lesion from an endoscopic image, the endoscopic images associated with the respective pieces of findings-diagnosis information are classified into corresponding groups of the respective pieces of findings-diagnosis information. The endoscopic images are displayed and switched on a group-by-group basis by using tabs.

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: A medical image processing device having a processor configured to: acquire a medical image including an image of a subject; perform a first recognition of the medical image using a first recognizer; determine a confidence level for a recognition result of a first recognition by the first recognition; and perform a second recognition of the medical image using a second recognizer according to the confidence level for the recognition result of the first recognition, the second recognition having higher recognition accuracy than the first recognition.

Abstract: 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.

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: 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 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: 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: A bar is displayed in a second region. Display of the bar starts in a longest state when an undetected state in which a region of interest is not detected transitions to a detected state in which the region of interest is detected, and display in the longest state is maintained until the detected state transitions to the undetected state. When the detected state transitions to the undetected state, the bar is reduced in length over time. When a predetermined time elapses, the length of the bar becomes 0, and the bar disappears. In addition, in a case where the undetected state transitions to the detected state before the bar disappears, the length of the bar returns to the longest.