Canon Kabushiki Kaisha

Daisuke Furukawa

Bin Chen

Yoshihiko Iwase

Fukashi Yamazaki

Kenji Morita

Hiroshi Imamura

Keita Nakagomi

Akihiro Katayama

Masami Kawagishi

Yuta Nakano

Masahiro Yakami

Takeshi Kitamura

Ryo Sakamoto

An image processing apparatus according to the present invention includes a first classification unit configured to classify a plurality of pixels in two-dimensional image data constituting first three-dimensional image data including an object into a first class group by using a trained classifier, and a second classification unit configured to classify a plurality of pixels in second three-dimensional image data including the object into a second class group based on a result of classification by the first classification unit, the second class group including at least one class of the first class group. According to the image processing apparatus according to the present invention, a user's burden of giving pixel information can be reduced and a region can be extracted with high accuracy.

Image processing apparatus, image processing system, image processing method, and storage medium for classifying a plurality of pixels in two-dimensional and three-dimensional image data

A first extraction unit that extracts a region of a pulmonary nodule drawn in an image, a second extraction unit that extracts a region of a structure drawn in the image, a setting unit that sets a decision boundary to be at a position away from the pulmonary nodule region by a distance determined on a basis of a size of the pulmonary nodule region, a decision unit that decides whether or not the structure region extracted by the second extraction unit contacts with both a region related to the pulmonary nodule region and the decision boundary, and an acquisition unit that acquires, as a region of a desired structure, the structure region decided by the decision unit to contact with both the pulmonary nodule region and the decision boundary in the structure region extracted by the second extraction unit are included.

Image processing apparatus, image processing method, and program

An image processing apparatus includes a first extraction unit configured to extract a first target region from an image using a trained classifier, a setting unit configured to set region information to be used in a graph cut segmentation method based on a first extraction result including the first target region, a second extraction unit configured to extract a second target region using the graph cut segmentation method based on the set region information, and a generation unit configured to generate a ground truth image corresponding to the image based on a second extraction result including the second target region.

Image processing apparatus, image processing method, and non-transitory computer-readable storage medium

An image processing apparatus includes a first classification unit configured to classify each of a plurality of pixels included in a three-dimensional medical image using a first classifier for classifying each pixel into a plurality of classes including a class representing a first target region, a determination unit configured to determine an image region including the first target region and a second target region from the three-dimensional medical image based on a first classification result, a second classification unit configured to classify each of a plurality of pixels included in the determined image region using a second classifier for classifying each pixel into a plurality of classes including at least either one of a class representing the first target region and a class representing the second target region, and an integration unit configured to integrate the first and the second classification results to acquire a third classification result.

Image processing system, image processing method, and non-transitory storage medium

The present invention is to provide an apparatus presenting information serving as a reason for inference as information on findings so as to be easily recognized by a doctor. A medical diagnosis support apparatus infers a diagnostic name derived from a medical image based on image feature values indicating features of a region included in the medical image, acquires information on findings representing the features of the region included in the medical image based on the image feature values, and presents the information on the findings as a reason for the inference.

Medical diagnosis support apparatus, information processing method, medical diagnosis support system, and program

An image processing apparatus is configured to extract an object region from an image. The image processing apparatus includes: a setting unit configured to set a plurality of reference points in the image; an obtaining unit configured to obtain a contour of the object region corresponding to each of the plurality of reference points as an initial extraction result based on a characteristic of the object region; and an extraction unit configured to extract the object region from the image based on an integration result obtained by integrating values of pixels in a plurality of initial extraction results.

Image processing apparatus, image processing system, image processing method, and storage medium

An image processing system includes a first setting unit configured to set, in a learning image, a plurality of mutually different position coordinates belonging to a region of interest presenting a site of interest rendered in the learning image, an extracting unit configured to extract the region of interest by using the plurality of position coordinates, a calculating unit configured to calculate a feature value for determining an attribute of the site of interest from a plurality of extraction results of the region of interest corresponding to the plurality of position coordinates, and a constructing unit configured to construct an identifier for determining the attribute based on a plurality of the feature values corresponding to the plurality of extraction results of the region of interest and a correct answer value of the attribute of the site of interest rendered in the learning image.

Image processing system, apparatus, method and storage medium

An information processing apparatus includes an acquisition unit that acquires, in a medical image, a first region and a second region different from the first region, a limiting unit that limits extracting a third region, connecting the first region and the second region, within a range including an extraction direction determined based on the first region; and an extraction unit that extracts the third region within the range limited by the limiting unit.

Information processing apparatus, extraction method, and medium

An image processing apparatus comprises generating unit configured to generate a second image by changing a size of a first image such that a region of interest in the second image satisfies a predetermined criterion about a dimension; and extracting unit configured to extract the region of interest from the second image generated by the generating unit, by applying a Graph-Cut method using a Graph-Cut coefficient corresponding to the criterion to the second image.

Image processing apparatus, image processing method, and image processing system for extracting regions of interest

A boundary of a site included as an attached abnormal shadow in a medical image is corrected to allow assisting in diagnosis based on a shape of a tissue. An image processing apparatus according to the present invention includes: a boundary extraction unit configured to extract a boundary of a first site and a boundary of a second site in the medical image; a boundary identification unit configured to identify a partial boundary of the first site that is adhere to the boundary of the second site as a first boundary part, and to identify a partial boundary of the first site that is not adhere to the boundary of the second site as a second boundary part; and a correction unit configured to correct a shape of the first boundary part based on the second boundary part.

An image processing apparatus comprising, boundary extraction means for detecting boundaries of retina layers from a tomogram of an eye to be examined, exudate extraction means for extracting an exudate region from a fundus image of the eye to be examined, registration means for performing registration between the tomogram and the fundus image, and calculating a spatial correspondence between the tomogram and the fundus image, specifying means for specifying a region where an exudate exists in the tomogram using the boundaries of the retina layers, the exudate region, and the spatial correspondence, likelihood calculation means for calculating likelihoods of existence of the exudate in association with the specified region, and tomogram exudate extraction means for extracting an exudate region in the tomogram from the specified region using the likelihoods.

Image processing apparatus for processing a tomogram of an eye to be examined, image processing method, and computer-readable storage medium

An image processing apparatus, which analyzes retina layers of an eye to be examined, comprising, means for extracting a feature amount, which represents an anatomical feature in the eye to be examined, from a projection image obtained from a tomogram of the retina layers and a fundus image of the eye to be examined, means for determining a type of the anatomical feature based on the feature amount, means for deciding layers to be detected from the retina layers according to the determined type of the anatomical feature, and detecting structures of the decided layers in the tomogram, and means for modifying the structure of the layer included in a region having the anatomical feature of the structures of the layers detected by the layer structure detection means.

Image processing apparatus, control method, and computer readable storage medium for analyzing retina layers of an eye

In a tomographic image photographing apparatus, a deformation of a volume image is corrected accurately even if an object to be inspected moves when the volume image is acquired. An image processing apparatus acquires a tomographic image of the object to be inspected from combined light beams of return light beams, which is obtained by irradiating the object to be inspected with a plurality of measuring light beams, and corresponding reference light beams. In the image processing apparatus, a photographing unit obtains a tomographic image of a fundus with the plurality of measuring light beams, and a detection unit detects a retina layer from the tomographic image. Based on the detected retina layer, a fundus shape is estimated. Based on the estimated fundus shape, a positional deviation between tomographic images is corrected.

Image processing apparatus and method for correcting deformation in a tomographic image

An information processing apparatus that selects a plurality of feature amounts acquired by applying a filter to learning data and generates a discriminator based on the selected feature amounts includes a time specification unit configured to specify a calculation time required for acquiring a feature amount of a selection candidate by applying the filter to the selected feature amounts or the learning data, a precision specification unit configured to specify a precision of a discriminator generated based on the feature amount of the selection candidate and the selected feature amounts, a selection unit configured to select the feature amount of the selection candidate based on the calculation time and the precision, and a generation unit configured to generate the discriminator based on the selected feature amounts.

Information processing apparatus and information processing method

An image processing apparatus for supporting imaging diagnosis of an eye is provided. A layer boundary of a retina region is detected from a tomographic image. A position where the detected layer boundary intersects with an upper or lower limit position of the image in the depth direction of the tomographic image is determined as a dividing position. The tomographic image is divided at the determined dividing position by a scan line in the depth direction of the tomographic image. Subsequently, whether the detection is a false detection is judged for each divided region. An average density value of the image outside the retina region according to the detected result is calculated for each divided region, and the detection in the divided region is judged to be a false detection if the average density value is equal to or greater than a predetermined threshold.

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Tokyo, Japan

Daisuke Furukawa