Abstract: An image processing apparatus includes a processor. The processor is configured to acquire image information from an endoscope during observation of an inside of a subject, generate an organ model from the acquired image information, identify an unobserved region that is not observed by the endoscope in the organ model, estimate a top and a bottom and an azimuth of an image pickup visual field of the endoscope with respect to the organ model, set a display direction of the organ model based on the top and the bottom and the azimuth of the image pickup visual field, and output the organ model to the monitor, the organ model being associated with the identified unobserved region.

Abstract: An image processing apparatus for endoscope includes a processor. The processor sequentially receives a plurality of observation images of an endoscope, detects one or more lesioned parts from each of the plurality of observation images, analyzes visibility of at least one of a distance from the endoscope, an occupied area, a shape, a size, a position in the observation image, a color, luminance, or an organ part relating to the detected lesioned part, sets a display extension time of a detection result of the lesioned part according to the visibility, and outputs the observation image to which the detection result of the lesioned part is added.

Abstract: An image processing apparatus includes a processor including hardware, the processor being configured to: estimate, based on image information from a medical device that includes at least an endoscope, a plurality of procedure actions of an operator of the endoscope; perform different supports respectively for procedures by the operator, according to an estimation result of the procedure actions; and output a display for the supports to a display.

Abstract: A training data generating system includes a processor. The processor acquires a plurality of medical images. The processor associates medical images with each other which are included in the plurality of medical images based on similarities of an imaging target to generate an associated image group including medical images associated with each other. The processor outputs, to a display, an application target image to be an image as an application target of representative training information based on the associated image group. The processor accepts input of representative contour information indicative of a contour of a specific region in the application target image as the representative training information. The processor applies contour information, as training information, to each medical image included in the associated image group based on the representative training information input to the application target image.

Abstract: An image processing apparatus includes an input unit, an estimation unit, an acquisition unit, a production unit, and a display control unit. The input unit acquires examination information including an endoscope image. The estimation unit estimates an image pickup site based on the endoscope image. The acquisition unit acquires, from the examination information, image pickup information corresponding to the endoscope image and indicating a state of at least one of an endoscope or a subject when the endoscope image is picked up. The production unit produces a model map and associates the image pickup information with a virtual site based on a result of the estimation by the estimation unit. The display control unit controls a display device.

Abstract: An endoscopic image processing apparatus includes a processor. The processor performs processing for acquiring lesion information including information indicating a position of a lesion region included in an endoscopic image, determines whether the lesion region is included in the endoscopic image, and performs processing for generating a display image for displaying one or more marks in at least one of N mark display regions set as regions as many as a maximum display number of the one or more marks, and generating the one or more marks indicating in which reference region among a predetermined plurality of reference regions set in the endoscopic image a present position of the lesion region or a position of the lesion region immediately before the detection is interrupted is included and displaying the one or more marks in at least one of the N mark display regions.

Abstract: An image processing apparatus have a processor configured to: receive a plurality of images of a tissue including a lesion portion, the plurality of images being received from an endoscope; judge, based on a signal from the endoscope, whether or not to engage a differentiation classification operation; in response to judging that the differentiation classification operation is engaged, process the plurality of images to specify the lesion portion within one or more of the plurality of images; and perform differentiation classification on the one or more images to classify the lesion portion into at least one class of a plurality of classes; and in response to judging that the differentiation classification operation is not engaged, not process the plurality of images to specify the lesion portion within the one or more of the plurality of images.

Abstract: An image processing apparatus for endoscope includes a processor. The processor sequentially receives a plurality of observation images of an endoscope, detects one or more lesioned parts from each of the plurality of observation images, analyzes visibility of at least one of a distance from the endoscope, an occupied area, a shape, a size, a position in the observation image, a color, luminance, or an organ part relating to the detected lesioned part, sets a display extension time of a detection result of the lesioned part according to the visibility, and outputs the observation image to which the detection result of the lesioned part is added.

Abstract: An image processing device includes a processor comprising hardware, wherein the processor is configured to execute: acquiring intraluminal images; generating, for each of the intraluminal images, lesion information by estimating a visual point with respect to a lesion region extracted from each of the intraluminal images and analyzing a three-dimensional structure of the lesion, the lesion information indicating any of a top portion, a rising portion, and a marginal protruding portion in the lesion region; and extracting, based on the lesion information, a target image satisfying a prescribed condition from the intraluminal images.

Abstract: An image processing apparatus includes a processor including hardware, the processor being configured to: estimate, based on image information from a medical device that includes at least an endoscope, a plurality of procedure actions of an operator of the endoscope; perform different supports respectively for procedures by the operator, according to an estimation result of the procedure actions; and output a display for the supports to a display.

Abstract: An image processing apparatus have a processor configured to: receive a plurality of images of a tissue including a lesion portion, the plurality of images being received from an endoscope; judge, based on a signal from the endoscope, whether or not to engage a differentiation classification operation; in response to judging that the differentiation classification operation is engaged, process the plurality of images to specify the lesion portion within one or more of the plurality of images; and perform differentiation classification on the one or more images to classify the lesion portion into at least one class of a plurality of classes; and in response to judging that the differentiation classification operation is not engaged, not process the plurality of images to specify the lesion portion within the one or more of the plurality of images.

Abstract: An image processing device includes a processor including hardware, the processor being configured to execute: estimating an operation state of a medical apparatus in a lumen of a subject based on information sequentially input from the medical apparatus, the medical apparatus including an imaging device, and an insertion portion inserted into the lumen, and the information including at least an intraluminal image obtained by the imaging device capturing an image inside the lumen; and performing processing corresponding to the operation state of the medical apparatus in the lumen based on an estimation result.

Abstract: An image processing apparatus includes: a processor comprising hardware, the processer being configured to execute: setting, in an image, an area of interest where classification is evaluated; calculating surface layer structure information representing a surface layer structure in the area of interest; calculating at least focus degrees of the outside of the area of interest in the image; and classifying the image based on the surface layer structure information and the focus degrees of the outside of the area of interest.

Abstract: An image processing apparatus including a processor comprising hardware, wherein the processor is configured to execute: analyzing a characteristic of a pathologic region included in individual endoscopic images of an endoscopic image group arranged in chronological order; setting, based on the characteristic of the pathologic region, an extraction condition for extracting one or more endoscopic images appropriate for diagnosis from the endoscopic image group; and extracting, based on the extraction condition, one or more endoscopic images having image quality appropriate for diagnosis from the endoscopic image group. When performing the analysis of the characteristic of the pathologic region, the processor classifies the pathologic region into a preset class of malignant degree.

Abstract: An image processing device includes a processor comprising hardware, wherein the processor is configured to execute: acquiring intraluminal images; generating, for each of the intraluminal images, lesion information by estimating a visual point with respect to a lesion region extracted from each of the intraluminal images and analyzing a three-dimensional structure of the lesion, the lesion information indicating any of a top portion, a rising portion, and a marginal protruding portion in the lesion region; and extracting, based on the lesion information, a target image satisfying a prescribed condition from the intraluminal images.

Abstract: Provided is an information processing system configured to: receive a plurality of images; select a standard image; search, in extracting partial images for complementing a too bright region/too dark region in the standard image from a reference images, using correction images obtained by subjecting each of the images to multivalued processing for each division of luminance components, for regions having matching shapes of respective regions included in the correction image of the standard image and the correction images of the other images; and complement image portions corresponding to the too bright region and/or too dark region in the correction image of the standard image using image portions, which are matching regions and correspond to appropriately bright regions, to thereby generate a synthetic image.

Abstract: Provided is an information processing system configured to: receive a plurality of images; select a standard image; search, in extracting partial images for complementing a too bright region/too dark region in the standard image from a reference images, using correction images obtained by subjecting each of the images to multivalued processing for each division of luminance components, for regions having matching shapes of respective regions included in the correction image of the standard image and the correction images of the other images; and complement image portions corresponding to the too bright region and/or too dark region in the correction image of the standard image using image portions, which are matching regions and correspond to appropriately bright regions, to thereby generate a synthetic image.

Abstract: A voice control system for managing home electrical appliances includes a home agent server (HAS) connected to the home electrical appliances, a microphone and a speaker linked to the agent server through an in-house network. An transaction processing (TP) program runs on HAS and interprets the user's voice request to find a destined appliance and a manner of control the same, and performs the requested control to the destined appliance. The result is notified to the user by means of a voice message.

Abstract: A voice control system for managing home electrical appliances includes a home agent server (HAS) connected to the home electrical appliances, a microphone and a speaker linked to the agent server through an in-house network. An transaction processing (TP) program runs on HAS and interprets the user's voice request to find a destined appliance and a manner of control the same, and performs the requested control to the destined appliance. The result is notified to the user by means of a voice message.