Abstract: The invention is directed to a reduction in the influence on a pathological diagnosis when an image reading apparatus is exchanged. In order to solve the above-mentioned problem, there is provided an image processing apparatus that processes a biological image generated by capturing an image of a biological specimen in an image reading apparatus, including: an acquisition unit that acquires identification information of the image reading apparatus; a determination unit that determines a type of biological tissue included in the biological image; and a correction unit that adds a correction process to the biological image in correspondence with the identification information of the image reading apparatus and the type of biological tissue.

Abstract: A cell feature amount calculating apparatus is provided that is capable of capturing the state of nuclear DNA. This cell feature amount calculating apparatus includes an image input unit that inputs an image of a cell, a cell nucleus region extracting unit that extracts a cell nucleus region of the cell from the image, a standard contour length calculating unit that calculates a standard contour length of the cell nucleus region, a contour length sequence calculating unit that extracts, for each threshold value of a plurality of different threshold values, a specific region which is a region having a pixel value larger than or equal to the threshold value from the cell nucleus region and calculating a contour length sequence by calculating a contour length of the specific region, and a contour complexity calculating unit that calculates a feature amount of the cell based on the standard contour length and the contour length sequence.

Abstract: A pathological tissue image capturing system includes a pathological image acquirer 100 for capturing a pathological tissue image and an output device 120 for outputting the pathological tissue image. The pathological tissue image capturing system also includes a weighting device 111 for detecting a ROI from the pathological tissue image and adding a weight to pixels positioned in the ROI, and a range selector 112 for selecting an enlarged image capturing range in which to capture the pathological tissue image at an enlarged scale based on the weight added by the weighting device 111. The pathological image acquirer 100 captures an enlarged pathological tissue image in the enlarged image capturing range selected by the range selector 112. The output device 120 outputs the captured enlarged pathological tissue image in the enlarged image capturing range.

Abstract: A method of evaluating a cell state based on information of an image taken of a cell containing a chromosome territory is provided. This method includes extracting the chromosome territory from the image (S20), standardizing a positioning state of the chromosome territory and then quantifying the positioning state (S22), and evaluating the cell state based on the quantified positioning state of the chromosome territory (S26).

Abstract: A cell feature amount calculating apparatus is provided that is capable of capturing the state of nuclear DNA. This cell feature amount calculating apparatus includes an image input unit that inputs an image of a cell, a cell nucleus region extracting unit that extracts a cell nucleus region of the cell from the image, a standard contour length calculating unit that calculates a standard contour length of the cell nucleus region, a contour length sequence calculating unit that extracts, for each threshold value of a plurality of different threshold values, a specific region which is a region having a pixel value larger than or equal to the threshold value from the cell nucleus region and calculating a contour length sequence by calculating a contour length of the specific region, and a contour complexity calculating unit that calculates a feature amount of the cell based on the standard contour length and the contour length sequence.

Abstract: A pathological diagnosis support device, a pathological diagnosis support program, a pathological diagnosis support method, and a pathological diagnosis support system extract a pathological tissue for diagnosis from a pathological image and diagnose the pathological tissue. A tissue collected in a pathological inspection is stained using, for example, hematoxylin and eosin. In consideration of the state of the tissue in which a cell nucleus and its peripheral constituent items are stained in respective colors unique thereto, subimages such as a cell nucleus, a pore, cytoplasm, interstitium are extracted from the pathological image, and color information of the cell nucleus is also extracted. The subimages and the color information are stored as feature candidates so that presence or absence of a tumor and benignity or malignity of the tumor are determined.

Abstract: A spot quantification apparatus includes an image input unit, a filtering unit, and a spot quantification unit. The image input unit receives an image including a spot. The filtering unit filters the image input through the image input unit a plurality of times while changing a parameter of a kernel within a predetermined range. The spot quantification unit quantifies a feature of the spot based on the luminance distribution in each image which has been filtered a plurality of times by the filtering unit.

Abstract: A pathological tissue image capturing system includes a pathological image acquirer 100 for capturing a pathological tissue image and an output device 120 for outputting the pathological tissue image. The pathological tissue image capturing system also includes a weighting device 111 for detecting a ROI from the pathological tissue image and adding a weight to pixels positioned in the ROI, and a range selector 112 for selecting an enlarged image capturing range in which to capture the pathological tissue image at an enlarged scale based on the weight added by the weighting device 111. The pathological image acquirer 100 captures an enlarged pathological tissue image in the enlarged image capturing range selected by the range selector 112. The output device 120 outputs the captured enlarged pathological tissue image in the enlarged image capturing range.

Abstract: The picture region extraction method coarse-grains this picture data space, calculates a coarse-grained empirical probability distribution, initializes parameters, calculates a coarse-grained conditional probability distribution and a class membership probability, updates the parameters, and calculates an evaluation function, each process being repeated until there is no change in the evaluation function, at which point, a picture region is extracted based on the class membership probability.

Abstract: A method of evaluating a cell state based on information of an image taken of a cell containing a chromosome territory is provided. This method includes extracting the chromosome territory from the image (S20), standardizing a positioning state of the chromosome territory and then quantifying the positioning state (S22), and evaluating the cell state based on the quantified positioning state of the chromosome territory (S26).

Abstract: A pathological diagnosis support device, a pathological diagnosis support program, a pathological diagnosis support method, and a pathological diagnosis support system extract a pathological tissue for diagnosis from a pathological image and diagnose the pathological tissue. A tissue collected in a pathological inspection is stained using, for example, hematoxylin and eosin. In consideration of the state of the tissue in which a cell nucleus and its peripheral constituent items are stained in respective colors unique thereto, subimages such as a cell nucleus, a pore, cytoplasm, interstitium are extracted from the pathological image, and color information of the cell nucleus is also extracted. The subimages and the color information are stored as feature candidates so that presence or absence of a tumor and benignity or malignity of the tumor are determined.

Abstract: A contour extraction method and apparatus is disclosed by which a contour can be extracted automatically at a high speed with a high degree of accuracy without the necessity to set a threshold value explicitly. In the contour extraction method and apparatus, from picture image data of a picture image including an image of a body which makes an object of contour extraction, region belonging probabilities with which individual points of the picture image belong to regions are calculated not based on values themselves of the image data but based on attributes of the points of the picture image. Then, the regions to which the individual points of the picture image belong are delimited using the region belonging probabilities, and then a boundary between the regions is extracted as a contour.

Abstract: The picture region extraction method coarse-grains this picture data space, calculates a coarse-grained empirical probability distribution, initializes parameters, calculates a coarse-grained conditional probability distribution and a class membership probability, updates the parameters, and calculates an evaluation function, each process being repeated until there is no change in the evaluation function, at which point, a picture region is extracted based on the class membership probability.

Abstract: Obtaining fast dipole size estimation with less influence of noise by using a regional dipole model. An artificial neural network section 30 executes regional dipole size estimation using a neural network having coupling coefficients representing coupling states among as plurality of units and thresholds thereof.

Abstract: An electrophysiological activity estimation method is used to estimate active areas of a selected part of a living body (e.g., human brain). Based on electromagnetic field distribution measured on a surface of the selected part of the living body as well as its shape, the method assumes each equivalent current dipole as a source of electromagnetic field distribution. At first, grid points are created to cover the selected part of the living body (e.g., head). Using the pseudoinverse, the method performs estimation of dipole distribution for equivalent current dipoles. Then, the equivalent current dipoles are subjected to sorting based on a priority order. An evaluation function (e.g., structural risk) is calculated in accordance with a square error between the measured electromagnetic field distribution and a theoretical value of electromagnetic field distribution caused by the equivalent current dipole, as well as a number of measuring points and a number of equivalent current dipoles.

Abstract: A live body internal condition predicting and expressing system is capable of predicting the internal condition of a live body on the basis of an electromagnetic field distribution at significantly reduced period.

Abstract: A trained neural network is used, for estimating the number, positions or moments of one or more dipoles which are assumed as sources of the electromagnetic field distribution based upon an electromagnetic field distribution of a living body or an object. At least either one of the dipole number, positions and moments or more than two of their combination is referred to as dipole parameters.