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 10 includes a medical image acquisition unit 11 that acquires a medical image 50 including a subject image, a medical image analysis result acquisition unit 12 that acquires an analysis result obtained by analyzing the medical image 50, a display unit 13 that displays at least one medical image 50 and at least information on presence or absence of a lesion or a type of a lesion in the analysis result acquired by the medical image analysis result acquisition unit 12, and an input receiving unit 14 that receives an input regarding whether or not the information on presence or absence of a lesion or a type of a lesion included in the analysis result is correct.

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: Provided are a medical image processing device, an endoscope system, and a method of operating a medical image processing device that can enhance the reliability for recognition results obtained by recognition processing in a case where a lesioned part or the like is diagnosed by recognition processing of artificial intelligence (AI). Comparison between a first medical image and a second medical image to be a comparison target with respect to the first medical image is performed. A specific medical image selected in accordance with a result of the comparison from among the second medical images is acquired. A monitor displays a plurality of recognition results that are obtained from recognition processing that is performed with respect to the specific medical image and performed for recognizing the observation target.

Abstract: Provided are an image processing device, an endoscope system, an image processing method, and a program capable of automatically differentiating a medical image including a scene of interest and supporting saving of the medical image according to a differentiation result.

Abstract: The system control unit functions as a captured image data acquisition unit that acquires captured image data obtained by imaging the inside of a subject with an endoscope; a visual-line detection unit 44B that detects a visual line directed to a display device that displays a captured image based on the captured image data; a processing unit that performs recognition processing for performing detection of a lesion site from the captured image data and identification of the detected lesion site on the captured image data; and a display control unit for causing the display device to display a result of the recognition processing by the processing unit. The processing unit controls the content of the recognition processing on the captured image data on the basis of the visual line detected by the visual-line detection unit.

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: 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: 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: A medical image processing apparatus includes a recognition unit that detects a region of interest from a medical image and classifies the region of interest, a display control unit that causes emphasis display of the region of interest and a classification for the region of interest to be displayed in a screen for displaying the observation target, and a change determining unit that determines at least any of whether to change a display style of the emphasis display or whether to change a display style of the classification. The display control unit changes the display style of the emphasis display in the case where it is determined to change the display style of the emphasis display and changes the display style of the classification in the case where it is determined to change the display style of the classification.

Abstract: A medical-use image processing device including: an image acquisition unit that acquires a medical-use image; a determination unit that determines an illumination mode at the time when the medical-use image is captured; a recognition unit that performs a first recognition for the medical-use image in a case where determination is made that the illumination mode is a first illumination mode, and performs a second recognition for the medical-use image in a case where determination is made that the illumination mode is a second illumination mode; and a display control unit that causes a display device to display a first display according to a result of the first recognition in a case where the determination is made that the illumination mode is the first illumination mode, and causes the display device to display a second display according to a result of the second recognition in a case where the determination is made that the illumination mode is the second illumination mode.

Abstract: There are provided a learning apparatus and a learning method that can facilitate creation of teaching data and prevent overtraining. A learning apparatus (10) includes a first database that stores a first image set in which a first image for learning and coordinate information for identifying a region larger than a region of interest included in the first image are associated with each other, and a second database that stores a second image set in which a second image for learning and second mask data for identifying a region of interest included in the second image are associated with each other. In a case of using the first image set to update a parameter of a CNN (32) (in a case of performing learning), a mask data creation unit (38) creates first mask data on the basis of the coordinate information for identifying the region larger than the region of interest.

Abstract: Provided are an endoscope apparatus, an endoscope processor, and a method for operating the endoscope apparatus in which illumination light (observation mode) is automatically switched in response to detection of a detection target from an image to reduce the burden of an operator's switching operation. An endoscope sequentially captures images of a subject in a first observation mode in which first illumination light (white light) is used. It is determined whether a detection target is continuously detected from the sequentially captured images. If it is determined that the detection target is continuously detected, the observation mode is automatically switched to a second observation mode in which second illumination light (special light) is emitted. In response to an elapse of a certain period of time after the observation mode is switched to the second observation mode, the observation mode is automatically switched from the second observation mode to the first observation mode.

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: An object of the present invention is to provide a learning apparatus and a learning method capable of appropriately learning pieces of data that belong to the same category and are acquired under different conditions. In a learning apparatus according a first aspect of the present invention, first data and second data are respectively input to a first input layer and a second input layer that are independent of each other, and feature quantities are calculated. Thus, the feature quantity calculation in one of the first and second input layers is not affected by the feature quantity calculation in the other input layer. In addition to feature extraction performed in the input layers, each of a first intermediate feature quantity calculation process and a second intermediate feature quantity calculation process is performed at least once in an intermediate layer that is shared by the first and second input layers.

Abstract: There are provided a medical image processing apparatus, a medical image processing method, a machine learning system, and a program that can reduce the volume of communication and can reduce the processing load of retraining or additional training that is performed by a machine learning apparatus.

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.

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: 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: 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.