Abstract: A medical support device includes: a processor; and a memory connected to or built into the processor, and the processor acquires target input data which is input data related to a disease of a subject candidate for a clinical trial of a drug, and a clinical trial period, inputs the target input data and the clinical trial period to a machine learning model trained using supervised training data including accumulated input data related to a disease at two or more points in time and a time interval of the input data, and causes the machine learning model to output a prediction result regarding the disease of the subject candidate in the clinical trial period, and outputs selection reference information for determining whether or not to select the subject candidate as a subject for the clinical trial, according to the prediction result.

Abstract: The invention provides a making method of modified polyvinyl alcohol embolic microspheres. First, polyvinyl alcohol dimethyl sulfoxide solution is added to acryloyl chloride dichloromethane solution for reaction, then taurine solution is added to the above solution for further reaction, so that functional groups are introduced into the side chains of polyvinyl alcohol, then blank microspheres are prepared by suspension crosslinking method, and finally, drug-loaded modified polyvinyl alcohol embolic microspheres are prepared. The invention aims at improving the drug loading rate and drug loading speed of the microspheres. Through modification, the crystallinity of polyvinyl alcohol is weakened, the swelling in water is accelerated, and the application effect of the microspheres is improved.

Abstract: The invention provides a making method of modified polyvinyl alcohol embolic microspheres. First, polyvinyl alcohol dimethyl sulfoxide solution is added to acryloyl chloride dichloromethane solution for reaction, then taurine solution is added to the above solution for further reaction, so that functional groups are introduced into the side chains of polyvinyl alcohol, then blank microspheres are prepared by suspension crosslinking method, and finally, drug-loaded modified polyvinyl alcohol embolic microspheres are prepared. The invention aims at improving the drug loading rate and drug loading speed of the microspheres. Through modification, the crystallinity of polyvinyl alcohol is weakened, the swelling in water is accelerated, and the application effect of the microspheres is improved.

Abstract: There is provided a diagnosis support device including a processor and a memory connected to or built in the processor, in which the processor is configured to: acquire a medical image; extract a plurality of anatomical regions of an organ from the medical image; input images of the plurality of anatomical regions to a plurality of feature amount derivation models prepared for each of the plurality of anatomical regions, and output a plurality of feature amounts for each of the plurality of anatomical regions from the feature amount derivation models; input the plurality of feature amounts which are output for each of the plurality of anatomical regions to a disease opinion derivation model, and output a disease opinion from the disease opinion derivation model; and present the opinion.

Abstract: A diagnosis support device includes a processor and a memory connected to or built in the processor. The processor is configured to perform non-linear registration processing of a target image which is a medical image to be analyzed and at least one representative image generated from a plurality of medical images, input at least one of transformation amount information of the target image obtained by the non-linear registration processing or a feature amount derived from the transformation amount information to a disease opinion derivation model, and output a disease opinion from the disease opinion derivation model.

Abstract: An image processing apparatus includes: a processor; and a memory connected to or built in the processor. The processor is configured to generate, as learning data used for training a machine learning model for medical images and examination results of medical examinations, new medical images from a first medical image and a second medical image among a plurality of the medical images according to a generation condition, and generate new examination results by performing calculation based on the generation condition on a first examination result of the medical examination corresponding to the first medical image and a second examination result of the medical examination corresponding to the second medical image.

Abstract: An image processing apparatus includes a processor and a memory connected to or built in the processor. The processor is configured to perform non-linear registration processing on a first medical image and a second medical image among a plurality of medical images, and generate at least one new medical image that is used for training a machine learning model for the medical images by transforming at least one medical image of the first medical image or the second medical image based on a result of the non-linear registration processing.

Abstract: This application relates to a node group-based data processing method performed by a first node in the node group, and includes: constructing, according to a first user identifier, a mapping relationship for mapping the first user identifier to a target value; performing homomorphic encryption on a mapping parameter of the mapping relationship, to obtain a mapping parameter ciphertext, and transferring the mapping parameter ciphertext to the second node in the node group; receiving the reference value and the fragment information returned by the second node; and maintaining, when a result obtained after homomorphic decryption is performed on the reference value is consistent with the target value, the fragment information returned corresponding to the reference value, and triggering the first node to collect fragment information maintained in each first node, to aggregate the collected fragment information to obtain a user identifier intersection set of the node group.

Abstract: The medical information display apparatus includes a first data acquisition unit that acquires a table showing relevance between at least one item included in clinical diagnostic information on dementia and a brain area, a second data acquisition unit that acquires clinical diagnostic information on dementia of a subject, an image acquisition unit that receives an input of a three-dimensional brain image, a brain area division unit that divides the three-dimensional brain image of the subject, an image analysis unit that calculates an analysis value for each brain area, an operation unit that selects one item among items included in the clinical diagnostic information of the subject, a display unit, and a display controller that specifies a brain area corresponding to the one item selected by the operation unit and displays brain area specifying information for specifying the specified brain area and an analysis value of the brain area.

Abstract: There are provided an information output apparatus, an information output method, and an information output program capable of outputting information effective for diagnosis or evaluation of dementia. In a case where a brain area having a high atrophy rate is input, the information output apparatus can output a test item highly relevant to the input brain area using a first table T1 that stores the relevance between a plurality of divided brain areas of a brain image and a plurality of test items of a dementia diagnostic test. In addition, in a case where a test item of interest is input, a brain area highly relevant to the input test item can be output.

Abstract: A medical image processing apparatus having a processor configured to detect at least four reference landmarks among the left eye, the right eye, the diencephalon, the fornix, the corpus callosum, the left hippocampus, and the right hippocampus from a brain image, performs first registration including registration by similarity transformation using reference landmarks between the brain image and a standard brain image, and perform second registration by nonlinear transformation between the brain image and the standard brain image after the first registration.

Abstract: Provided are an information processing device, a program, a trained model, a diagnostic support device, a learning device, and a prediction model generation method that can perform prediction with high accuracy using images. An information processing device includes: an information acquisition unit that receives an input of image data and non-image data related to a target matter; and a prediction unit that predicts an aspect related to the matter at a time different from a time when the image data is captured on the basis of the image data and the non-image data input through the information acquisition unit.

Abstract: The medical information display apparatus includes an image acquisition unit that acquires a first brain image which is a brain image of a subject captured at a first time point and a second brain image captured at a second time point later in time than the first time point, a registration unit that performs registration between the first and the second brain image, an image analysis unit that extracts a first cavity region and a second cavity region from the first brain image and the second brain image, respectively, a display unit, and a display controller displays, a cavity expansion part included in a first non-cavity region, which is a region other than the first cavity region, and included in the second cavity region in a distinguishable manner from a region other than the cavity expansion part from a result of the registration between the first and second brain image.

Abstract: A brain image normalization apparatus, having a processor configured to: detect at least four reference landmarks of a left eye, a right eye, a diencephalon, a fornix, a corpus callosum, a left hippocampus, and a right hippocampus from a brain image including a brain of a subject; perform registration between the detected reference landmarks and reference landmarks corresponding to the detected reference landmarks included in a standard brain image; and normalize the brain image based on a result of the registration.

Abstract: A medical image display apparatus includes an image acquisition unit that receives an input of a three-dimensional brain image of a subject, a brain area division unit that divides the three-dimensional brain image of the subject into a plurality of brain areas, an image analysis unit that calculates an analysis value for each brain area from the three-dimensional brain image of the subject, a data acquisition unit that acquires information indicating a correspondence between the brain area and a function of the brain, a display unit, and a display controller that displays an image showing the brain image of the subject divided into the brain areas, a function of the brain corresponding to each of the brain areas, and the analysis value on the display unit in association with each other.

Abstract: A division unit 22 divides a brain included in a first brain image into a plurality of regions by performing registration between the first brain image including a brain of a subject and a standard brain image divided into a plurality of regions. A registration unit 23 performs registration between the first brain image and a second brain image that includes the brain of the subject and has a different imaging date and time from the first brain image. A change amount acquisition unit 24 acquires the amount of change from a corresponding region in the brain included in the first brain image, for at least one region of the plurality of regions in the brain included in the second brain image, based on the registration result.

Abstract: There is provided a medical information acquisition device including an information acquisition unit that acquires functional change information obtained on the basis of a reference image and a past image acquired by capturing images of the same subject at a reference time and a past time closer to the past than the reference time, respectively, using a trained model.

Abstract: A medical image processing apparatus, having a processor configured to divide brains included in a brain image and a standard brain image into a plurality of regions corresponding to each other, calculate a first correction amount between the pixel value of a first reference pixel included in each of the plurality of region in the brain image and the pixel value of a second reference pixel and a second correction amount for matching first other pixel values other than the first reference pixel included in each of the plurality of regions in the brain image with pixel values of second other pixels, and correct the brain image based on the first correction amount and the second correction amount.

Abstract: In a medical image processing apparatus, a medical image processing method, and a medical image processing program, in a case where there are a plurality of past brain images, it is possible to select a past brain image with which the atrophy rate of the brain can be accurately calculated. An image acquisition unit acquires a target brain image Bt as a diagnostic target and a plurality of past brain images Bpi, which have earlier imaging dates and times than the target brain image Bt, for the same subject. A similarity calculation unit calculates the similarity between each of the plurality of past brain images Bpi and a standard brain image Bs. A selection unit selects a reference brain image B0 serving as a reference for calculating the amount of change of the brain from the plurality of past brain images Bpi.

Abstract: The medical information display apparatus includes an image acquisition unit that acquires a first brain image which is a brain image of a subject captured at a first time point and a second brain image captured at a second time point later in time than the first time point, a registration unit that performs registration between the first and the second brain image, an image analysis unit that extracts a first cavity region and a second cavity region from the first brain image and the second brain image, respectively, a display unit, and a display controller displays, a cavity expansion part included in a first non-cavity region, which is a region other than the first cavity region, and included in the second cavity region in a distinguishable manner from a region other than the cavity expansion part from a result of the registration between the first and second brain image.