Abstract: An image processing apparatus includes: a surface shape estimation unit configured to estimate a surface shape of a target that appears in an intraluminal image of a living body; an imaging viewpoint changing unit configured to change an imaging viewpoint with respect to the surface shape from an imaging viewpoint used for estimation; and an image generation unit configured to generate a virtual image of the target for a case of imaging the target from the changed imaging viewpoint.

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: A diagnosis support apparatus performs identification for a plurality of support items, which are identification classifications about diagnosis support, and the diagnosis support apparatus is provided with a processor. The processor performs analysis processing for acquiring analysis results including an analysis result about an observation mode by analyzing at least one of an input signal specifying the observation mode and an observation image obtained by observing an inside of a subject with an endoscope; performs support item setting processing for setting a support item corresponding to the analysis results obtained by the analysis processing, among the plurality of support items, which are the identification classifications; and generates diagnosis support information, which is information used for diagnosis of a legion candidate area included in the observation image, based on an identification index corresponding to the set support item and the observation image.

Abstract: An image processing device includes a processor. The processor detects a lesion candidate based on a medical image obtained by picking up an image of a subject, detects a feature including a swelling direction of the lesion candidate, determines a display state of a mark displayed according to the feature of the lesion candidate, generates mark display information including information on the display state, and determines a position of the mark in a predetermined peripheral region of the lesion candidate according to the detected swelling direction. The image processing device generates a display image in which the mark is added to the position of the mark of the medical image based on the mark display information.

Abstract: An endoscope diagnosis support system includes a processor. The processor performs detection of an anomaly candidate area from an endoscope image obtained by performing image pickup of an inside of a subject to obtain a detection result, and generates a display image in which an indicator indicating detection of the anomaly candidate area is arranged in a periphery portion of the endoscope image in accordance with the detection result.

Abstract: An image processing apparatus includes a processor including hardware. The processor is configured to evaluate, based on information including an image which is captured by an endoscope and is sequentially input, a technical level of an operator who operates the endoscope, and measure a transit time of a specific section.

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 includes: a narrowband image acquisition unit configured to acquire a narrowband image showing inside of a lumen; a white light image acquisition unit configured to acquire a white light image showing the inside of the lumen; and a composite image generation unit configured to combine information of the narrowband image to the white light image, according to a depth of a submucosal object, to generate a composite image for display.

Abstract: An image processing device includes at least one processor having hardware. The processor is configured to implement analyzing, in an intraductal image which is an image of inside of a duct, an intraductal imaging situation based on a position of a subject relative to a part that captures an image of the subject. Next, the processor is calculating a plurality of specific region discrimination indices for the intraductal image. Finally, the processor is detecting a specific region by integral determination on the plurality of specific region discrimination indices depending on the intraductal imaging situation.

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 luminal shooting situation analysis unit configured to analyze a luminal shooting situation determined based on a relationship between a subject and an imaging unit that shoots the subject in a luminal image obtained by shooting an inside of a lumen; and a specific region detection unit configured to detect a specific region in accordance with the luminal shooting situation.

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 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: Example embodiments of the present invention relate to an image processing apparatus. The apparatus may include a processor and memory storing instructions that when executed on the processor cause the processor to perform the operations of detecting a deep region of a duct in an image and extracting a plurality of contour edges of an inner wall of the duct in the image. The apparatus then may identify a plurality of convex regions among the plurality of contour edges, analyze a respective curvature of each of the plurality of convex regions to identify a convex direction for each of the plurality of convex regions, and detect, as an abnormal region, a convex region having a convex direction directed toward the deep region.

Abstract: An image processing apparatus includes: a memory; and a processor comprising hardware, the processor being configured to output a result of classifying an image group to be classified based on a result of main learning performed based on a result of preliminary learning and a target image group to be learned, the preliminary learning being performed based on a similar image group similar in at least one of characteristics of a shape of an object in the target image group, a tissue structure of an object in the target image group, and an imaging system of a device that captures the target image group, wherein the similar image group is different from the image group to be classified in the main learning.

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 detection unit configured to detect images of interest including regions of interest that are estimated as an object to be detected, from a group of a series of images acquired by sequentially imaging a lumen of a living body; an image-of-interest group extracting unit configured to extract a group of images of interest including an identical region of interest, from the images of interest detected by the detection unit; and a representative image extracting unit configured to extract one or more representative images from the group of images of interest, based on at least one of correlation of the regions of interest with the object to be detected, and visibility of the regions of interest.

Abstract: An image processing apparatus includes: an abnormality candidate region detection unit that detects an abnormality candidate region based on a contour edge of a mucosal wall or a surface shape of the mucosal wall in an intraluminal image of a body; and an abnormal region specifying unit that specifies an abnormal region based on texture information of the abnormality candidate region.

Abstract: An image processing apparatus includes: a blood vessel sharpness image creation unit configured to create a blood vessel sharpness image representing sharpness of a blood vessel region in which a blood vessel is shown in an intraluminal image; an abnormal candidate region extraction unit configured to extract a region in which the sharpness is decreased in the blood vessel sharpness image, as a candidate region for an abnormal region in which a visible vascular pattern is locally lost; and an abnormal region determination unit configured to determine whether the candidate region is an abnormal region, based on extension information indicating a state of the blood vessel region extending in a neighborhood of the candidate region.