Abstract:
An information processing device includes: a plurality of identifiers that discriminates whether abnormal data that is information indicating an abnormal value is included in treatment data and detects the abnormal data; and a hardware processor that: customizes evaluation data used when evaluating discrimination accuracy of the plurality of identifiers; calculates the discrimination accuracy of each of the plurality of identifiers using the evaluation data customized by the hardware processor; and selects one identifier out of the plurality of identifiers as an identifier used for discrimination based on a calculation result by the hardware processor.
Abstract:
A radiographic image capturing system includes the following. A capturing stand includes a holder to hold radiographic image capturing devices. A radiation irradiator irradiates the radiographic image capturing devices loaded in the holder at once. An image processor generates a plurality of images based on image data acquired by the radiographic image capturing devices. The image processor removes a streaky component residing in the generated image to correct the image. Such process includes forming a smoothed image by smoothing with a low-pass filter, and subtracting an interpolation image to extract a streaky image from the smoothing image and adding the streaky image to remove the streaky component. The smoothing includes reflecting smoothing on pixels showing a subject structure using a low-pass filter with a size larger in the horizontal direction compared to pixels other than pixels showing the subject structure.
Abstract:
Techniques for efficiently generating time-varying image data for use in training a machine learning model are disclosed. An aspect of the present disclosure relates to a machine learning model trained using training data that includes at least one piece of training time-varying image data of second time-varying image data and third time-varying image data, the second time-varying image data being obtained by standardizing first time-varying image data in a time direction, the first time-varying image data being based on a reception signal for image generation received by an ultrasound probe, third time-varying image data being based on the second time-varying image data, and, and ground truth data including a detection target corresponding to the at least one piece of training time-varying image data.
Abstract:
An ultrasound image processing apparatus includes a reception section that receives an ultrasound image and discriminator determination information from an external apparatus, the ultrasound image being generated based on a reception signal acquired by an ultrasound probe that transmits and receives an ultrasound wave to and from a subject, the discriminator determination information allowing determination of a discriminator that discriminates a target in the ultrasound image, and one or more first hardware processors, in which the one or more first hardware processors determine one from among a plurality of discriminators to which the ultrasound image is to be input, the one discriminator being determined based on the discriminator determination information, input the ultrasound image to the determined discriminator to acquire a discrimination result to be output from the determined discriminator.
Abstract:
An information processing apparatus including: a classifier that is applied for medical treatment data; and a hardware processor that sets a property of the classifier, evaluates a sufficiency level of the property by using evaluation data for the classifier, and selects and sets one classifier as the classifier to be used in a facility by referring to an evaluation result.
Abstract:
A combination group includes combinations of elements belonging to items. When an attention location in a medical image is designated, two or more elements corresponding to the attention location and belonging to the first item are identified. When one of the two or more elements is designated, two or more elements belonging to a second item and included in one or more combinations of elements included in the combination group and corresponding to the designated one element are displayed to be distinguishable from the other elements. When one or more of the two or more displayed elements are designated, one or more elements belonging to a third item and included in at least one combination of elements included in the combination group and corresponding to a combination of the one designated element and each of the one or more designated elements are displayed to be distinguishable from the other elements.
Abstract:
A medical diagnosis support system including a hardware processor configured with a program to perform operations including: operation as an acquisition part configured to acquire lifestyle habit information of a subject; operation as an estimation part configured to estimate, using a trained identifier, future lung function of the subject from information on the subject, the information on the subject including the lifestyle habit information acquired from the acquisition part; and operation as a control part configured to control an output part to output a result that has been estimated by the estimation part.
Abstract:
Provided is a learning data set generation device of the present disclosure, which causes a computer to execute: acquiring second medical imaging data generated by predetermined image conversion processing on first medical imaging data; and generating a pair of the second medical imaging data and a first ground truth label, which is a ground truth label for the first medical imaging data, as a learning data set.
Abstract:
An image diagnostic technique using a machine learning model is disclosed. An aspect of the present disclosure relates to a machine learning model trained by using training data that includes first ultrasound image data based on a reception signal received by an ultrasound probe; first ground truth data that is first region information associated with a detection target of the first ultrasound image data; and second ground truth data that is first position information associated with the detection target of the first ultrasound image data or that is second region information based on the first position information.
Abstract:
An information processing apparatus including: a classifier that is applied for medical treatment data; and a hardware processor that sets a property of the classifier, evaluates a sufficiency level of the property by using evaluation data for the classifier, and selects and sets one classifier as the classifier to be used in a facility by referring to an evaluation result.