Abstract: As a technique enabling to simply and accurately diagnose human T cell leukemia virus type 1 (HTLV-1) related disease, there is provided a diagnostic method for an HTLV-1 related disease based on an amount of tumor necrosis factor receptor 2 (TNFR2) in a blood sample taken from a subject, wherein (1) it is determined based on an increase of the amount of TNFR2 that the subject suffers from, or is likely to develop, the HTLV-1 related disease; and/or (2) it is determined based on a decrease of the amount of TNFR2 that the subject is in remission, or is likely to be in remission, of the HTLV-1 related disease.

Abstract: As a technique enabling to simply and accurately diagnose human T cell leukemia virus type 1 (HTLV-1) related disease, there is provided a diagnostic method for an HTLV-1 related disease, comprising the steps of: measuring the amount of a marker protein in a blood sample taken from a subject, wherein the marker protein is at least one selected from the proteins listed in Tables 1 and 2; and, if a measured value is a predetermined reference value or more or the predetermined reference value or less, determining that the subject suffers from the HTLV-1 related disease or determining that the subject is in remission of the HTLV-1 related disease.

Abstract: A method of ranking epitopes derived from neoantigens as targets for personalized immunotherapy includes collecting candidate epitopes based on patient data of a cancer patient. A set of scores are calculated for each of the candidate epitopes, each of the scores in a respective one of the sets for a respective one of the candidate epitopes representing an independent measure of a likelihood of the respective one of candidate epitopes to elicit an immune response in the cancer patient. The scores in each of the sets of scores are combined into a single score for each of the candidate epitopes. The single scores for the candidate epitopes in each case reflect an overall likelihood of eliciting the immune response in the patient. The candidate epitopes are ranked using the single scores for the immunotherapy.

Abstract: An information processing apparatus (2000) extracts a histomorphological feature of a tissue included in pathological image data (10). The information processing apparatus (2000) generates prediction data (30) based on the extracted histomorphological feature. The prediction data (30) indicates one or more of a prediction relating to an effect of a cancer therapeutic drug on a target patient and a prediction of a side effect of the cancer therapeutic drug on the target patient.

Abstract: When making a diagnosis by synthetically taking into account the information obtained by preparing a plurality of samples using different staining methods or the like and sequentially observing the samples, a diagnostician must remember information about the plurality of samples. The present invention includes image storage means for storing a reference image obtained by photographing a predetermined stained sample of and a comparison image obtained by photographing another stained sample of substantially identical biological tissues, partial image creation means for detecting a structure of the biological tissue from the reference image, cutting out from the comparison image a partial image that contains the structure detected, and storing into partial image storage means the partial image in association with the structure and the comparison image, image output means for outputting a result image that includes the reference image and the partial image, and the partial image storage means.

Abstract: The present invention provides an information processing apparatus capable of accurately separating parenchymal cells and stromal cells from each other regardless of the staining intensity of the cells. The information processing apparatus is an information processing apparatus 100 including: an image processing unit 110 for smoothing a tissue sample image 150 obtained by staining and then imaging a biological tissue containing parenchymal cells 151 and stromal cells 152 so that luminance values of cell components of each of the parenchymal cells 151 become less than those of each of the stromal cells 152; and a mask generation unit 120 for generating, through generating a binary image by binarizing the tissue sample image 115 smoothed by the image processing unit 110, a mask 125 for removing a region of the stromal cells from the tissue sample image 115.

Abstract: Luminance calculation means 81 calculates luminance of a cell nucleus extracted from an antinuclear antibody image of a designated dilution ratio. Titer prediction means 82 predicts an antinuclear antibody titer, using a staining pattern specified from a staining form of the cell nucleus and the luminance at at least one dilution ratio.

Abstract: The present invention provides an information processing apparatus capable of selecting a region of cancer cells in any tissue sample image and easily and accurately counting the number of the cancer cells. The information processing apparatus is an information processing apparatus 100 including: an acquisition unit 110 for acquiring image data obtained by reading a tissue sample image 150 obtained by putting a mark 151 specifying a selected area 152 on an image obtained by immunostaining and then imaging a biological tissue; and a counting unit 120 for counting the number of cancer cells in the selected area 152 specified by the mark 151 based on the image data of the tissue sample image 150 acquired by the acquisition unit 110, wherein a diagnosis based on the tissue sample image 150 is supported.

Abstract: Luminance calculation means 81 calculates luminance of a cell nucleus extracted from an antinuclear antibody image of a designated dilution ratio. Titer prediction means 82 predicts an antinuclear antibody titer, using a staining pattern specified from a staining form of the cell nucleus and the luminance at at least one dilution ratio.

Abstract: A partial image extracting unit extracts images of a predetermined size and constant magnification from a tissue region. A mask generating unit generates a mask for removing a region not intended for measurement from the tissue region for each extracted image. A complete mask generating unit generates a temporary complete mask in which the masks generated for each of the images are integrated together, and generates a complete mask in which close portions among unmasked portions in the temporary complete mask are unified into one or more target regions. A measuring unit measures information pertaining to an object to be measured included in the image, and this information is measured for each of the images extracted by the partial image extracting unit. A region information calculating unit calculates, for each target region, information pertaining to the object to be measured from the measured information and from the complete mask.

Abstract: When making a diagnosis by synthetically taking into account the information obtained by preparing a plurality of samples using different staining methods or the like and sequentially observing the samples, a diagnostician must remember information about the plurality of samples. The present invention includes image storage means for storing a reference image obtained by photographing a predetermined stained sample of and a comparison image obtained by photographing another stained sample of substantially identical biological tissues, partial image creation means for detecting a structure of the biological tissue from the reference image, cutting out from the comparison image a partial image that contains the structure detected, and storing into partial image storage means the partial image in association with the structure and the comparison image, image output means for outputting a result image that includes the reference image and the partial image, and the partial image storage means.

Abstract: The present invention provides an information processing apparatus capable of accurately separating parenchymal cells and stromal cells from each other regardless of the staining intensity of the cells. The information processing apparatus is an information processing apparatus 100 including: an image processing unit 110 for smoothing a tissue sample image 150 obtained by staining and then imaging a biological tissue containing parenchymal cells 151 and stromal cells 152 so that luminance values of cell components of each of the parenchymal cells 151 become less than those of each of the stromal cells 152; and a mask generation unit 120 for generating, through generating a binary image by binarizing the tissue sample image 115 smoothed by the image processing unit 110, a mask 125 for removing a region of the stromal cells from the tissue sample image 115.

Abstract: The present invention provides an information processing apparatus capable of accurately separating parenchymal cells and stromal cells from each other regardless of the staining intensity of the cells. The information processing apparatus is an information processing apparatus 100 including: an image processing unit 110 for smoothing a tissue sample image 150 obtained by staining and then imaging a biological tissue containing parenchymal cells 151 and stromal cells 152 so that luminance values of cell components of each of the parenchymal cells 151 become less than those of each of the stromal cells 152; and a mask generation unit 120 for generating, through generating a binary image by binarizing the tissue sample image 115 smoothed by the image processing unit 110, a mask 125 for removing a region of the stromal cells from the tissue sample image 115.

Abstract: The present invention provides an information processing apparatus capable of selecting a region of cancer cells in any tissue sample image and easily and accurately counting the number of the cancer cells. The information processing apparatus is an information processing apparatus 100 including: an acquisition unit 110 for acquiring image data obtained by reading a tissue sample image 150 obtained by putting a mark 151 specifying a selected area 152 on an image obtained by immunostaining and then imaging a biological tissue; and a counting unit 120 for counting the number of cancer cells in the selected area 152 specified by the mark 151 based on the image data of the tissue sample image 150 acquired by the acquisition unit 110, wherein a diagnosis based on the tissue sample image 150 is supported.

Abstract: A partial image extracting unit extracts images of a predetermined size and constant magnification from a tissue region. A mask generating unit generates a mask for removing a region not intended for measurement from the tissue region for each extracted image. A complete mask generating unit generates a temporary complete mask in which the masks generated for each of the images are integrated together, and generates a complete mask in which close portions among unmasked portions in the temporary complete mask are unified into one or more target regions. A measuring unit measures information pertaining to an object to be measured included in the image, and this information is measured for each of the images extracted by the partial image extracting unit. A region information calculating unit calculates, for each target region, information pertaining to the object to be measured from the measured information and from the complete mask.

Abstract: Disclosed is an information processing apparatus that supports diagnosis based on a tissue sample image obtained from imaging a biological tissue, including: a tissue sample image cutting unit that individually cuts out the tissue sample image from a plurality of slides that includes the plurality of tissue sample images; and a display position setting unit that sets a display position on a display screen where a reduced image of each tissue sample image is displayed, on the basis of a characteristic amount of each tissue sample image cut by the tissue sample image cutting unit.

Abstract: Provided is an information processing apparatus which supports diagnosis based on a tissue specimen image obtained by capturing body tissues, including an area generation unit that divides at least one feature value of the tissue specimen image into a plurality of levels based on a magnitude of the feature value, and generates an area on the tissue specimen image belonging to each level; and an overlay image generation unit that associates the area of each level which is generated by the area generation unit with an image which is processed to have the same shape and the same positional relation as the area and in which a magnitude relation of the feature value is identifiable and generates an overlay image.

Abstract: A support system for histopathological diagnosis includes a cell nucleus uniformity evaluation unit evaluating a uniformity of a plurality of cell nuclei included in a ductal region in an image. With this configuration, there is provided a support system, a support method and a support program for histopathological diagnosis, which enables realization of highly accurate cancer differentiation in a pathological diagnosis.

Abstract: This invention is directed to improvement of the accuracy of cancer differentiation in the pathologic diagnosis using a pathologic tissue image analysis. There are included a stroma area/duct area detecting module for detecting, from a biological tissue image, a duct area on the basis of duct characteristic information indicating the characteristic of ducts included in a tissue area in the biological tissue image; an intraduct cell-nucleus detecting module for extracting, based on a predetermined pigment reference, cell nucleuses included in the detected duct area; and a duct formation evaluating module for calculating a heterotypic degree of each duct on the basis of the distribution state of the cell nucleuses for a predetermined base areas in each duct.

Abstract: The present invention provides an information processing apparatus capable of selecting a region of cancer cells in any tissue sample image and easily and accurately counting the number of the cancer cells. The information processing apparatus is an information processing apparatus 100 including: an acquisition unit 110 for acquiring image data obtained by reading a tissue sample image 150 obtained by putting a mark 151 specifying a selected area 152 on an image obtained by immunostaining and then imaging a biological tissue; and a counting unit 120 for counting the number of cancer cells in the selected area 152 specified by the mark 151 based on the image data of the tissue sample image 150 acquired by the acquisition unit 110, wherein a diagnosis based on the tissue sample image 150 is supported.