Abstract:
An image processing device includes: an abnormality candidate region detection unit configured to detect, from an intraluminal image obtained by imaging a living body lumen, an abnormality candidate region in which a tissue characteristic of the living body or an in-vivo state satisfies a predetermined condition; a feature data calculation unit configured to calculate, from each of a plurality of regions inside the intraluminal image, a plurality of pieces of feature data including different kinds; an integrated feature data calculation unit configured to calculate integrated feature data by integrating the plurality of pieces of feature data based on information of the abnormality candidate region; and a detection unit configured to detect an abnormality from the intraluminal image by using the integrated feature data.
Abstract:
An image processing apparatus includes: a candidate region detection unit configured to detect, from an image acquired by imaging inside a lumen of a living body, a candidate region for a specific region that is a region where a specific part in the lumen has been captured; a candidate region information acquiring unit configured to acquire information related to the candidate region detected by the candidate region detection unit; an identification means determination unit configured to determine an identification means for identification of, based on the information related to the candidate region, whether or not the candidate region is the specific region; and an identification unit configured to identify whether or not the candidate region is the specific region by using the identification means determined by the identification means determination unit.
Abstract:
An image processing apparatus processes an image obtained by capturing inside of a lumen of a living body. The image processing apparatus includes: a contour edge region extracting unit configured to extract a contour edge region of an examination target from the image; an examination region setting unit configured to set an examination region in the image so as not to include the contour edge region; and an abnormal structure identifying unit configured to identify whether a microstructure of a surface of the examination target is abnormal, based on texture information of the examination 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 apparatus includes: a contour extracting unit configured to extract a plurality of contour pixels from an image acquired by capturing an inside of a lumen of a living body; a feature data calculating unit configured to calculate feature data based on pixel values of the plurality of contour pixels and positional relationship among the plurality of contour pixels; and an abnormal portion detecting unit configured to detect an abnormal portion in the lumen based on the feature data.
Abstract:
An image processing device includes: a specific candidate area extracting unit configured to extract a specific candidate area that satisfies a predetermined condition from an intraluminal image captured inside a body lumen; a reference area setting unit configured to set a reference area that includes at least a part of the specific candidate area; a local area extracting unit configured to extract local areas based on the reference area; a local feature data calculator configured to calculate local feature data that is feature data of each of the local areas; a weight setting unit configured to set a weight depending on each of the local areas based on the specific candidate area; and a feature data integrating unit configured to integrate the local feature data.
Abstract:
An image processing apparatus includes: a region-of-interest setting unit configured to set a region of interest in an image; a linear convex region extracting unit configured to extract, from the region of interest, a linear region having a predetermined number or more of continuously-arranged pixels whose pixel values are higher than pixel values of neighboring pixels; an intra-region curvature feature data computing unit configured to compute curvature feature data based on curvatures of one or more arcs along the linear region; and an abnormality determining unit configured to determine whether there is an abnormal portion in the region of interest, based on a distribution of the curvature feature data.
Abstract:
An image processing apparatus for processing an image acquired by imaging a living body includes: a blood vessel candidate region extraction unit configured to extract a plurality of blood vessel candidate regions from the image; an identical blood vessel candidate region extraction unit configured to extract, from among the plurality of blood vessel candidate regions, a blood vessel candidate region group estimated to form a line shape when integrated, as an identical blood vessel candidate region; an evaluation value calculation unit configured to calculate one or more kinds of evaluation values for evaluating a likelihood that the identical blood vessel candidate region corresponds to an identical blood vessel; and a blood vessel region discrimination unit configured to discriminate whether or not the identical blood vessel candidate region forms an identical blood vessel region, based on the evaluation values.
Abstract:
An information processing system includes a processor that performs an object detection to detect an object from a detection target image. The processor divides the detection target image into a group of first grid cells. The object is positioned to overlap a group of second grid cells included in the group of the first grid cells. At this time, the processor generates a bounding box in a respective second grid cell included in the group of the second grid cells. The processor surrounds a portion of the object positioned in the respective second grid cell with the bounding box generated in the respective second grid cell and displays, on a display, a position and shape of the object by a collection of a plurality of bounding boxes superimposedly on the detection target image.
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.