Abstract: A medical image processing apparatus of the present invention includes: a three-dimensional model estimating section for estimating a three-dimensional model of an object based on a two-dimensional image of an image of the object which is inputted from a medical image pickup apparatus; an image dividing section for dividing the two-dimensional image into a plurality of regions each of which includes at least one or more pixels; a feature value calculation section for calculating a feature value according to a grayscale of each pixel in one region for each of the plurality of regions; and a lesion detection reference setting section for setting lesion detection reference for detecting a locally protruding lesion in the regions of the three-dimensional model which correspond to each of the plurality of regions, based on the feature value according to the grayscale.

Abstract: A medical image processing apparatus which performs image processing on a medical input image, includes: a pixel extraction portion for extracting an inappropriate pixel satisfying a predetermined condition in the input image, a replacing pixel information calculation portion for calculating replacing information with which pixel information of the inappropriate pixel is to be replaced, based on pixel information of a predetermined region including the extracted inappropriate pixel or adjacent to the extracted inappropriate pixel and a replaced image generation portion for replacing the pixel information of the inappropriate pixel in the input image with the replacing information and generating a replaced image.

Abstract: An image processing device includes; a lesion candidate region detecting section that detects a lesion candidate region based on at least one color signal in a medical image including a plurality of color signals; an incidental region detecting section that detects an incidental region that arises because of incidental attributes accompanying a lesion from the medical image; and a detection standard changing section that changes a detection standard when detecting a lesion from the lesion candidate region in accordance with a detection result of the incidental region.

Abstract: A CPU executes a gray value gradient calculation process to, for example, an R signal in step S10, executes an isotropic change feature value calculation process based on a gray value gradient calculated in step S11, and further executes a possible polyp detection process for generating a possible polyp image at a location where a polyp exists based on an isotropic change feature value calculated in step S12. This improves the detection of an existing location of an intraluminal abnormal tissue.

Abstract: A CPU implements a possible polyp detection process of step S4 to execute processing for each label value of a thinned image and superimpose a processing result on a possible polyp image, thereby generating a possible polyp labeling image in which a possible polyp edge is labeled. The possible polyp labeling image, in which the possible polyp image is superimposed on an original image, is displayed on a display device so that a possible polyp location on the image can be easily checked, thereby improving the detection accuracy of an intraluminal abnormal tissue.

Abstract: An image processing apparatus includes: a surface model generation section for performing processing for generating a three-dimensional surface model from a two-dimensional medical image; and an area reliability calculation section for dividing the surface model into multiple areas and calculating the reliability of data in each of the multiple areas.

Abstract: A medical image processing apparatus of the present invention has a three-dimensional model estimating section for estimating, based on an inputted two-dimensional image of an image of a living tissue within a body cavity, a three-dimensional model of the living tissue, a shape feature value calculating section for calculating shape feature values of respective voxels included in the three-dimensional model of the living tissue, a three-dimensional shape extracting section for extracting a first voxel group whose three-dimensional model has been estimated as a predetermined shape, in the respective voxels included in the three-dimensional model of the living tissue, based on the shape feature values, and a protruding shape detecting section for detecting the first voxel group as a voxel group configuring a protruding shape in the three-dimensional model of the living tissue.

Abstract: Main parts of an endoscope system of the present invention include a medical observation apparatus, a medical image processing apparatus, and a monitor. A CPU of the medical image processing apparatus is constituted by function units including a three-dimensional model estimating unit, a detection target area setting unit, a shape feature value calculating unit, a three-dimensional shape detecting unit, a threshold determining unit, and a polyp determining unit. Such a configuration enables to execute a process appropriately adapted to an observation state of a targeted two-dimensional image and to improve the detection accuracy in the detection of a lesion with locally elevated shape as compared to the past.

Abstract: A medical image processing apparatus of the present invention includes an edge extracting section that extracts edges of an inputted two-dimensional image, a three-dimensional-model estimating section that estimates a three-dimensional model on the basis of the two-dimensional image, a voxel extracting section that extracts, on the basis of positions of respective voxels, where the edges are present, a predetermined voxel group to be set as a calculation object of a shape feature value, a shape-feature-value calculating section that calculates the shape feature value for at least a part of voxels among the predetermined voxel group, a three-dimensional-shape extracting section that extracts a voxel group, a three-dimensional model of which is estimated as a predetermined shape, on the basis of the shape feature value, and a tuberal-shape detecting section that detects the voxel group as a voxel group forming a tuberal shape in the three-dimensional model of the living tissue.

Abstract: A medical image processing apparatus of the invention comprises: a three-dimensional model estimating section that estimates a three-dimensional model of body tissues based on a two-dimensional image of an image of the body tissues inside a body cavity inputted from a medical image pickup apparatus; a voxel detecting section that detects one voxel existing on a nearest side in a view direction of the medical image pickup apparatus among the voxels included in the three-dimensional model; and a raised shape detecting section that acquires one curved surface including the one voxel to detect a position with gradient variation on the one curved surface and to determine whether or not body tissues with a locally raised shape exist in the position in the three-dimensional model.

Abstract: A medical image processing apparatus of the present invention includes: a three-dimensional model estimating section for estimating a three-dimensional model of an object based on a two-dimensional image of an image of the object which is inputted from a medical image pickup apparatus; an image dividing section for dividing the two-dimensional image into a plurality of regions each of which includes at least one or more pixels; a feature value calculation section for calculating a feature value according to a grayscale of each pixel in one region for each of the plurality of regions; and a lesion detection reference setting section for setting lesion detection reference for detecting a locally protruding lesion in the regions of the three-dimensional model which correspond to each of the plurality of regions, based on the feature value according to the grayscale.

Abstract: Main parts of an endoscope system of the present invention include a medical observation apparatus, a medical image processing apparatus, and a monitor. A CPU of the medical image processing apparatus is constituted by function units including a three-dimensional model estimating unit, a detection target area setting unit, a shape feature value calculating unit, a three-dimensional shape detecting unit, a threshold determining unit, and a polyp determining unit. Such a configuration enables to execute a process appropriately adapted to an observation state of a targeted two-dimensional image and to improve the detection accuracy in the detection of a lesion with locally elevated shape as compared to the past.

Abstract: A medical image processing apparatus of the invention comprises: a three-dimensional model estimating section that estimates a three-dimensional model of body tissues based on a two-dimensional image of an image of the body tissues inside a body cavity inputted from a medical image pickup apparatus; a voxel detecting section that detects one voxel existing on a nearest side in a view direction of the medical image pickup apparatus among the voxels included in the three-dimensional model; and a raised shape detecting section that acquires one curved surface including the one voxel to detect a position with gradient variation on the one curved surface and to determine whether or not body tissues with a locally raised shape exist in the position in the three-dimensional model.

Abstract: A medical image processing apparatus which performs image processing on a medical input image, includes: a pixel extraction portion for extracting an inappropriate pixel satisfying a predetermined condition in the input image, a replacing pixel information calculation portion for calculating replacing information with which pixel information of the inappropriate pixel is to be replaced, based on pixel information of a predetermined region including the extracted inappropriate pixel or adjacent to the extracted inappropriate pixel and a replaced image generation portion for replacing the pixel information of the inappropriate pixel in the input image with the replacing information and generating a replaced image.

Abstract: A CPU executes a gray value gradient calculation process to, for example, an R signal in step S10, executes an isotropic change feature value calculation process based on a gray value gradient calculated in step S11, and further executes a possible polyp detection process for generating a possible polyp image at a location where a polyp exists based on an isotropic change feature value calculated in step S12. This improves the detection of an existing location of an intraluminal abnormal tissue.

Abstract: An image processing apparatus includes: a surface model generation section for performing processing for generating a three-dimensional surface model from a two-dimensional medical image; and an area reliability calculation section for dividing the surface model into multiple areas and calculating the reliability of data in each of the multiple areas.

Abstract: A CPU implements a possible polyp detection process of step S4 to execute processing for each label value of a thinned image and superimpose a processing result on a possible polyp image, thereby generating a possible polyp labeling image in which a possible polyp edge is labeled. The possible polyp labeling image, in which the possible polyp image is superimposed on an original image, is displayed on a display device so that a possible polyp location on the image can be easily checked, thereby improving the detection accuracy of an intraluminal abnormal tissue.

Abstract: An image processing device includes; a lesion candidate region detecting section that detects a lesion candidate region based on at least one color signal in a medical image including a plurality of color signals; an incidental region detecting section that detects an incidental region that arises because of incidental attributes accompanying a lesion from the medical image; and a detection standard changing section that changes a detection standard when detecting a lesion from the lesion candidate region in accordance with a detection result of the incidental region.

Abstract: A medical image processing apparatus of the present invention has a three-dimensional model estimating section for estimating, based on an inputted two-dimensional image of an image of a living tissue within a body cavity, a three-dimensional model of the living tissue, a shape feature value calculating section for calculating shape feature values of respective voxels included in the three-dimensional model of the living tissue, a three-dimensional shape extracting section for extracting a first voxel group whose three-dimensional model has been estimated as a predetermined shape, in the respective voxels included in the three-dimensional model of the living tissue, based on the shape feature values, and a protruding shape detecting section for detecting the first voxel group as a voxel group configuring a protruding shape in the three-dimensional model of the living tissue.

Abstract: A medical image processing apparatus of the present invention includes an edge extracting section that extracts edges of an inputted two-dimensional image, a three-dimensional-model estimating section that estimates a three-dimensional model on the basis of the two-dimensional image, a voxel extracting section that extracts, on the basis of positions of respective voxels, where the edges are present, a predetermined voxel group to be set as a calculation object of a shape feature value, a shape-feature-value calculating section that calculates the shape feature value for at least a part of voxels among the predetermined voxel group, a three-dimensional-shape extracting section that extracts a voxel group, a three-dimensional model of which is estimated as a predetermined shape, on the basis of the shape feature value, and a tuberal-shape detecting section that detects the voxel group as a voxel group forming a tuberal shape in the three-dimensional model of the living tissue.