Abstract: An image acquisition unit (2020) acquires an analysis image. The analysis image is an image in which a plurality of cell nuclei in a lesion of a target person are captured. A feature-value calculation unit (2040) calculates the feature-value relating to the cell nuclei from the analysis image. An evaluation function acquisition unit (2060) acquires an evaluation function from an evaluation function storage unit (10). The evaluation function is a function with which prediction information is calculated based on the feature-value. The prediction information generation unit (2080) generates prediction information relating to a target person based on a feature-value, which has been calculated from an analysis image, and an evaluation function which has been acquired by the evaluation function acquisition unit (2060). The prediction information is information indicating a prediction of a prognosis of a disease of the target person or a prediction of malignancy of a disease of the target person.

Abstract: An image acquisition unit (2020) acquires an analysis image. The analysis image is an image in which a plurality of cell nuclei in a lesion of a target person are captured. A feature-value calculation unit (2040) calculates the feature-value relating to the cell nuclei from the analysis image. An evaluation function acquisition unit (2060) acquires an evaluation function from an evaluation function storage unit (10). The evaluation function is a function with which prediction information is calculated based on the feature-value. The prediction information generation unit (2080) generates prediction information relating to a target person based on a feature-value, which has been calculated from an analysis image, and an evaluation function which has been acquired by the evaluation function acquisition unit (2060). The prediction information is information indicating a prediction of a prognosis of a disease of the target person or a prediction of malignancy of a disease of the target person.

Abstract: A pathological diagnosis assisting apparatus according to the present invention provides the diagnosis assisting information for assisting diagnosis of tissue fibrosis from the image of the stained sample, and includes an image reading unit configured to read the image of the stained sample and an image processing unit configured to process the image. The image processing unit includes an image classification unit configured to classify the collagenous fiber and the elastic fiber, a tissue area extraction unit configured to extract a tissue area, an occupancy rate calculation unit configured to calculate the occupancy rates of the collagenous fiber and the elastic fiber in the tissue area, and a diagnosis assisting information providing unit configured to provide the diagnosis assisting information based on the calculated occupancy rates of the collagenous fiber and the elastic fiber.

Abstract: A pathological diagnosis assisting apparatus according to the present invention includes an image classification unit configured to classify at least one type of a specific substance, a tissue area extraction unit configured to extract a tissue area in the image of the sample, an image dividing unit configured to divide the tissue area into a plurality of sections, a specific substance occupancy rate calculation unit configured to, calculate an occupancy rate of the at least one type of the specific substance in each of the plurality of sections, and a diagnosis assisting information providing unit configured to determine an intermediate value of the occupancy rate of the specific substance from the calculated occupancy rates of the plurality of sections and to provide the intermediate value as the diagnosis assisting information.

Abstract: An image processing apparatus includes a first spectrum estimating unit for reading the image information from a storage unit and estimating a spectrum of an object based on the read image information; a dye amount estimating unit for estimating dye amounts included in the object using the estimated spectrum; a second spectrum estimating unit for synthesizing a first spectrum using the estimated dye amounts; a spectrum subtractor for calculating a difference spectrum by subtracting the first spectrum from the spectrum; a dye amount correcting unit for correcting at least a part of the estimated dye amounts; a third spectrum estimating unit for synthesizing a second spectrum using the corrected dye amount; a spectrum adder for synthesizing a third spectrum by adding the second spectrum and the difference spectrum; and an image synthesizer for synthesizing a display image from the third spectrum.

Abstract: An image processing apparatus includes a first spectrum estimating unit for reading the image information from a storage unit and estimating a spectrum of an object based on the read image information; a dye amount estimating unit for estimating dye amounts included in the object using the estimated spectrum; a second spectrum estimating unit for synthesizing a first spectrum using the estimated dye amounts; a spectrum subtractor for calculating a difference spectrum by subtracting the first spectrum from the spectrum; a dye amount correcting unit for correcting at least a part of the estimated dye amounts; a third spectrum estimating unit for synthesizing a second spectrum using the corrected dye amount; a spectrum adder for synthesizing a third spectrum by adding the second spectrum and the difference spectrum; and an image synthesizer for synthesizing a display image from the third spectrum.