Abstract: A radiographic image capturing device includes: a sensor substrate having one surface on which a plurality of light-receiving elements are two-dimensionally arranged; and a scintillator substrate that is arranged on the side of the light-receiving elements of the sensor substrate, wherein a region having no interface between insulating layers that differ in refractive index is formed between the scintillator substrate and incident planes of the light-receiving elements of the sensor substrate.

Abstract: A radiographic image capturing device includes: a sensor substrate having one surface on which a plurality of light-receiving elements are two-dimensionally arranged; and a scintillator substrate that is arranged on the side of the light-receiving elements of the sensor substrate, wherein a region having no interface between insulating layers that differ in refractive index is formed between the scintillator substrate and incident planes of the light-receiving elements of the sensor substrate.

Abstract: A breast cancer pathological image diagnosis support system for supporting a diagnosis of breast cancer based on a pathological image is provided. The breast cancer pathological image diagnosis support system includes an image obtaining unit which obtains an HE-stained image and an IHC image as pathological images to be diagnosed; an information obtaining unit which obtains information of a tumor area in the HE-stained image; a matching unit which calculates a matching position of the HE-stained image and the IHC image obtained by the image obtaining unit; a specifying unit which specifies a tumor area in the IHC image based on the information of the tumor area in the HE-stained image obtained by the information obtaining unit and information of the matching position calculated by the matching unit; and a calculating unit which calculates a staining positive cell content rate in the tumor area based on information of the tumor area in the IHC image specified by the specifying unit.

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: A radiation image capturing device includes scan lines, signal lines, radiation detection elements and switch elements. With respect to each of the radiation detection elements, a first distance between an edge of the radiation detection element and an edge of a scan line and/or a second distance between an edge of the radiation detection element and an edge of a signal line is set within a range acceptable as a manufacturing error. The center of the range is a value which maximizes a ratio obtained by dividing the area of the radiation detection element by a first parasitic capacitance between the radiation detection element and the scan line and/or a second parasitic capacitance between the radiation detection element and the signal line.

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 detection accuracy of poorly differentiated cancers in adenocarcinoma is improved by restricting false detection. Cell nucleus detection means 1 receives a digitized pathological image as an input and extracts the region of a cell nucleus therefrom. Gland duct detection means 2 detects a gland duct structure in the image. Poorly differentiated cancer detection means 4 detects poorly differentiated cancers only in the region other than the gland duct region. False detection rejection means 7 compares the detection density of poorly differentiated cancer in the vicinity of a detection point with a threshold that is predetermined depending on gland duct density in the vicinity of the detection point, at each detection point detected by poorly differentiated cancer detection means 4 and rejects the detection point as a false detection if the detection density of a poorly differentiated cancer is smaller than the threshold.

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: An evaluation system includes a capture unit for capturing an image of a living tissue in which HER2 protein and cell nucleuses are dyed, a discrimination unit for identifying a cell membrane from the image of the living tissue based on dyed cell nucleuses within the image of the living tissue captured by the capture unit to discriminate a dyed state of the cell membrane, and an evaluation unit for evaluating development of the HER2 protein based on a discrimination result by the discrimination unit.

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: 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 medicament for improving prognostic survival in therapy of malignant tumor is provided that may improve prognostic survival in DIC patients where the basal disease is malignant tumor, especially malignant tumor in hematopoietic organs. The medicament according to the invention comprises as a main active ingredient Activated Protein C, which is obtained from plasma or prepared by using the genetic recombination technique, and efficiently prolongs life-span of DIC patients where the basal disease is malignant tumor, especially malignant tumor in hematopoietic organs. In particular, the medicament may reduce adverse side effects of chemotherapeutics in chemotherapy of malignant tumor to enhance efficacy of said therapy and improve prognostic survival of patients suffering from malignant tumor.

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 breast cancer pathological image diagnosis support system for supporting a diagnosis of breast cancer based on a pathological image is provided. The breast cancer pathological image diagnosis support system includes an image obtaining unit which obtains an HE-stained image and an IHC image as pathological images to be diagnosed; an information obtaining unit which obtains information of a tumor area in the HE-stained image; a matching unit which calculates a matching position of the HE-stained image and the IHC image obtained by the image obtaining unit; a specifying unit which specifies a tumor area in the IHC image based on the information of the tumor area in the HE-stained image obtained by the information obtaining unit and information of the matching position calculated by the matching unit; and a calculating unit which calculates a staining positive cell content rate in the tumor area based on information of the tumor area in the IHC image specified by the specifying unit.

Abstract: Feature decision means (303) decides a set of features appropriate for pattern identification from a plenty of feature candidates generated by feature candidate generation means (302) by using learning patterns stored in learning, pattern storage means (301). The feature decision means (303) successively decides features according to a reference of information maximization under the condition that the decided feature is known while adding an effective noise to the learning pattern and performs information amount calculation approximately and at a high speed while merging the learning patterns into a set of N elements when required. As a result, it is possible to automatically create a feature set appropriate for pattern identification of a high performance without requiring enormous learning. Moreover, by using a transition table (305) containing transitions between sets, it is possible to perform pattern judgment with a high efficiency.

Abstract: An evaluation system includes a capture unit for capturing an image of a living tissue in which HER2 protein and cell nucleuses are dyed, a discrimination unit for identifying a cell membrane from the image of the living tissue based on dyed cell nucleuses within the image of the living tissue captured by the capture unit to discriminate a dyed state of the cell membrane, and an evaluation unit for evaluating development of the HER2 protein based on a discrimination result by the discrimination unit.

Abstract: The detection accuracy of poorly differentiated cancers in adenocarcinoma is improved by restricting false detection. Cell nucleus detection means 1 receives a digitized pathological image as an input and extracts the region of a cell nucleus therefrom. Gland duct detection means 2 detects a gland duct structure in the image. Poorly differentiated cancer detection means 4 detects poorly differentiated cancers only in the region other than the gland duct region. False detection rejection means 7 compares the detection density of poorly differentiated cancer in the vicinity of a detection point with a threshold that is predetermined depending on gland duct density in the vicinity of the detection point, at each detection point detected by poorly differentiated cancer detection means 4 and rejects the detection point as a false detection if the detection density of a poorly differentiated cancer is smaller than the threshold.

Abstract: A medicament for improving prognostic survival in therapy of malignant tumor is provided that may improve prognostic survival in DIC patients where the basal disease is malignant tumor, especially malignant tumor in hematopoietic organs. The medicament according to the invention comprises as a main active ingredient Activated Protein C, which is obtained from plasma or prepared by using the genetic recombination technique, and efficiently prolongs life-span of DIC patients where the basal disease is malignant tumor, especially malignant tumor in hematopoietic organs. In particular, the medicament may reduce adverse side effects of chemotherapeutics in chemotherapy of malignant tumor to enhance efficacy of said therapy and improve prognostic survival of patients suffering from malignant tumor.

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.