Abstract:
There are provided a learning apparatus, a learning method, an image processing apparatus, an endoscope system, and a program that enable generation of training data on the basis of output data from a learning model for which learning is performed by using normality data. A first learning model (500) is generated by performing first learning using normality data (502) as learning data or by performing first learning using as learning data, normality mask data (504) that is generated by making a part of normality data be lost, and second training data to be applied to a second learning model that identifies identification target data is generated by using output data output from the first learning model in response to input of abnormality data to the first learning model.
Abstract:
Provided are a learning device, a depth information acquisition device, an endoscope system, a learning method, and a program capable of efficiently acquiring a learning data set used for machine learning to perform depth estimation, and capable of implementing a highly accurate depth estimation for an actually imaged endoscope image. The learning device includes a processor performing endoscope image acquisition processing of acquiring an endoscope image obtained by imaging a body cavity with an endoscope system, actual measurement information acquisition processing of acquiring actually measured first depth information corresponding to at least one measurement point in the endoscope image, imitation image acquisition processing of acquiring an imitation image obtained by imitating an image of the body cavity to be imaged with the endoscope system, imitation depth acquisition processing of acquiring second depth information including depth information of one or more regions in the imitation image, and learning processing of causing a learning model to perform learning by using a first learning data set and a second learning data set.
Abstract:
An image acquisition unit sequentially acquires a medical image. A recognition processing unit applies a recognition process to the medical image. A recognition result display determination unit determines to display or not display the result of the recognition process on a display according to blur in the medical image. A display control unit controls the display of the recognition process according to the determination by the recognition result display determination unit.
Abstract:
Provided is a chromosome number determination method including: a step of performing multiplex PCR for simultaneously amplifying a plurality of loci on chromosomes using genomic DNA extracted from a single cell or a small number of cells as templates, in which the multiplex PCR includes a plurality of thermal cycles including thermal denaturation, annealing, and elongation, annealing time is longer than or equal to 90 seconds and shorter than 1,500 seconds in at least one of the plurality of thermal cycles, a plurality of primer sets used in the multiplex PCR are designed through a method for designing primer sets used in a polymerase chain reaction including a first stage selection step based on a local alignment score and a second stage selection step based on a global alignment score.
Abstract:
An endoscope system sequentially acquires a plurality of endoscopic images by continuously imaging an observation target. A recognition processing unit detects, from the acquired endoscopic images, regions including a lesion portion as regions-of-interest. A recognition result correction unit corrects a position of the region-of-interest of the specific image by using a position of the region-of-interest of a previous image acquired before the specific image and a position of the region-of-interest of a subsequent image acquired after the specific image.
Abstract:
In a learning device, method, and program for a discriminator, and a discriminator, it is possible to enable accurate learning of a discriminator that discriminates a state of an object to be observed, such as a cell. An image acquisition unit acquires a first image including an influence of a meniscus and a second image with the influence of the meniscus eliminated for the same object to be observed. Next, a training data generation unit generates training data for learning a discriminator based on the second image. Then, a learning unit learns the discriminator based on the first image and the training data.
Abstract:
There are provided an examination notification output device, an examination notification output method, an examination notification output program, and a gene chromosome examination system capable of outputting information, which is an indicator for determining whether or not a re-examination is required, in a case where it is determined that a re-examination is required for a gene chromosome examination. An examination notification output device that outputs an examination notification of a gene chromosome examination for examining the abnormalities of chromosomes included in embryonic cells includes: an information acquisition unit that acquires information including an examination result of a gene chromosome examination; an examination notification generation unit that generates an examination notification by adding re-examination necessity determination information that is used in determining whether or not a re-examination is required; and an examination notification output unit that outputs the generated examination notification.
Abstract:
There are included a colony evaluation unit 31 that acquires an evaluation result of the cell colony in a cell image obtained by imaging the cell colony, a divided region setting unit 32 that sets a plurality of divided regions by dividing the region of the cell colony according to the evaluation result, a display control unit 34 that displays each of the plurality of divided regions, and a region deformation unit 33 that deforms the divided regions according to a change in the form of the cell colony due to an operation on the cell colony. The display control unit 34 changes a display of the divided regions before the change in form of the cell colony to a display of the divided regions after the deformation.
Abstract:
A stem cell differentiation determination device includes an observation image acquisition unit that captures an image of an observation region including a stem cell in time series to acquire at least two observation images, a feature amount acquisition unit that acquires at least one feature amount of the stem cell for each observation image, a determination unit that determines whether or not the stem cell has been differentiated, on the basis of the feature amount, a change information acquisition unit that acquires information about a change in the feature amount between the observation images captured in time series or information about a change in a determination result from undifferentiation to differentiation between the observation images, and an output unit that outputs the information about a change in the feature amount or the information about a change in the determination result.