Abstract: To provide a high heat dissipation sheet that enables electrical insulation properties while also making possible a simple construction method. In the present invention, short fibers with electrical insulation properties and thermal conductive properties are electrostatically flocked at high density onto a substrate coated with adhesive, under conditions that allow for high density electrostatic flocking, the erect short fibers are adhered and fixed, binder resin is impregnated and is hardened, and subsequently one surface of the sheet is abraded so that the insulating and thermally conductive fibers penetrate and are arrayed at high density in the direction of the sheet thickness. As a result, a heat dissipation sheet is formed in which the fibers protrude from one surface while the opposite surface is made smooth so that heat from an exothermic material can be quickly absorbed by the opposite surface and quickly dissipated into the air by the fiber protrusion surface.

Abstract: A medical image processing device includes an input section to which a biological mucous membrane image obtained by picking up an image of a biological mucous membrane is inputted, a region extracting section that extracts a mucous membrane microstructure region corresponding to a mucous membrane microstructure from the inputted biological mucous membrane image, a closed region identifying section that identifies at least one closed region regarded as being surrounded by the mucous membrane microstructure region, and a unit region setting section that sets a biologically histological unit region on the basis of the mucous membrane microstructure region and the closed region.

Abstract: An image processing apparatus is provided with: a first feature value calculating section calculating a first feature value for each of pixels constituting an image obtained by picking up an image of a subject; a region dividing section dividing the image into multiple regions on the basis of the first feature values; a second feature value calculating section calculating a second feature value for each of the divided regions; a classification section performing classification with regard to which of multiple kinds of attributes each region of the multiple regions has, on the basis of the second feature value; a judgment section judging whether a region having a predetermined attribute exists or not; and a diagnostic support information calculating section correcting an attribute value of the region having the predetermined attribute to calculate diagnostic support information for supporting a diagnosis.

Abstract: A medical image processing apparatus includes a selection portion that selects a pixel of interest from an image composed of a plurality of pixels and obtained by picking up an image of a living tissue, a first feature value calculation portion that calculates a first feature value on the basis of color tone of the pixel of interest and color tones of surrounding pixels, a second feature value calculation portion that calculates a second feature value on the basis of the color tone of the pixel of interest and the color tones of surrounding pixels, an evaluation value calculation portion that calculates an evaluation value on the basis of the first feature value and the second feature value, and an evaluation value judgment portion that judges whether the pixel of interest is a pixel constituting the linear structure, on the basis of the evaluation value.

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 includes a selection portion that selects a pixel of interest from an image composed of a plurality of pixels and obtained by picking up an image of a living tissue, a first feature value calculation portion that calculates a first feature value on the basis of color tone of the pixel of interest and color tones of surrounding pixels, a second feature value calculation portion that calculates a second feature value on the basis of the color tone of the pixel of interest and the color tones of surrounding pixels, an evaluation value calculation portion that calculates an evaluation value on the basis of the first feature value and the second feature value, and an evaluation value judgment portion that judges whether the pixel of interest is a pixel constituting the linear structure, on the basis of the evaluation value.

Abstract: A plurality of images inputted in an image signal input portion are divided into a plurality of regions by an image dividing portion, and a feature value in each of the plurality of regions is calculated by a feature value calculation portion and divided into a plurality of subsets by a subset generation portion. On the other hand, a cluster classifying portion classifies a plurality of clusters generated in a feature space into any one of a plurality of classes on the basis of the feature value and occurrence frequency of the feature value. And a classification criterion calculation portion calculates a criterion of classification for classifying images included in one subset on the basis of a distribution state of the feature value in the feature space of each of the images included in the one subset.

Abstract: A plurality of images inputted in an image signal input portion are divided into a plurality of regions by an image dividing portion, and a feature value in each of the plurality of regions is calculated by a feature value calculation portion and divided into a plurality of subsets by a subset generation portion. On the other hand, a cluster classifying portion classifies a plurality of clusters generated in a feature space into any one of a plurality of classes on the basis of the feature value and occurrence frequency of the feature value. And a classification criterion calculation portion calculates a criterion of classification for classifying images included in one subset on the basis of a distribution state of the feature value in the feature space of each of the images included in the one subset.

Abstract: In order to reduce the amount of an organism attractant substance remaining inside concrete that tends be used wastefully and also to allow the organism attractant substance to effectively flow out gradually in a long period of time, an environmentally active, preserving and repairing-use concrete block is provided in which the air content and flowability of the concrete are increased, and the congregating and growing effects for fishes and shellfishes and the adhering and growing effects for algae are maintained so that a high attractant effect by odor of the organism attractant substance is obtained.

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 process for producing an optical compensation film comprises a liquid crystal layer application step (10) of applying a liquid crystal layer coating solution containing a liquid crystal compound to an alignment layer on a surface of a transparent substrate (4c) that is continuously transported; a liquid crystal layer drying step (11) of drying the liquid crystal layer; a cooling and curing step of curing the liquid crystal layer while cooling the liquid crystal layer to a temperature lower than a drying temperature used in the drying step; and a heating and curing step of curing the alignment layer while heating the alignment layer to a temperature higher than a cooling temperature used in the cooling and curing step. The process enables the durability and damage resistance as well as the optical characteristics of the optical compensation film to be independently controlled.

Abstract: A plurality of images inputted in an image signal input portion are divided into a plurality of regions by an image dividing portion, and a feature value in each of the plurality of regions is calculated by a feature value calculation portion and divided into a plurality of subsets by a subset generation portion. On the other hand, a cluster classifying portion classifies a plurality of clusters generated in a feature space into any one of a plurality of classes on the basis of the feature value and occurrence frequency of the feature value. And a classification criterion calculation portion calculates a criterion of classification for classifying images included in one subset on the basis of a distribution state of the feature value in the feature space of each of the images included in the one subset.

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: 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 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: An image processing apparatus according to the present invention includes a pixel selection unit adapted to select a pixel of interest from an image; a contrast feature value calculation unit adapted to calculate, as a contrast feature value, a value which represents an amount of change in contrast in a local region including the pixel of interest; a geometric feature value calculation unit adapted to calculate, as a geometric feature value, a value of an index which indicates whether or not a linear or massive structure is contained in the local region; an evaluation value calculation unit adapted to calculate an evaluation value by weighting each of the contrast feature value and the geometric feature value; and a region extraction unit adapted to extract a candidate region estimated to contain the linear or massive structure from the image based on a calculation result of the evaluation value.

Abstract: A medical image processing apparatus is a medical image processing apparatus performing image segmentation processing for a medical image including: a feature value calculating unit that calculates at least one feature value from the medical image; a category setting unit that sets, on the basis of the feature value calculated by the feature value calculating unit, plural categories in the medical image; a parameter setting unit that sets, on the basis of the feature value calculated by the feature value calculating unit, a parameter for each of areas of the medical image respectively classified into the categories set by the category setting unit; and an image segmenting unit that performs the image segmentation processing for the medical image according to an arithmetic operation of employing a dynamic contour model specified according to the number of categories set by the category setting unit and parameters set by the parameter setting unit.