Abstract: According to one embodiment, a learning apparatus includes a processor. The processor performs, on a neural network model, an adaptation processing that includes at least either insertion of an activation function, or correction of the activation function. The processor generates a trained model by training the neural network model on which the adaptation processing has been performed. The processor performs pruning on the trained model to generate a reconstructed model from which a parameter has been reduced.

Abstract: According to one embodiment, a learning apparatus includes a processor. The processor trains a neural network model having a plurality of pathways and generate a trained model. The processor performs pruning on the trained model and calculate a number of remaining parameters of each of the pathways. The processor generates a candidate model for reconstruction, the candidate model for reconstruction being generated by deleting a pathway in which the number of parameters is equal to or less than a threshold. The processor determines whether or not deletion of a further pathway included in the candidate model for reconstruction is possible. If it is determined that deletion of the further pathway is possible, the candidate model for reconstruction is subjected to each of the training, the pruning, and the generating.

Abstract: According to one embodiment, a learning system includes a plurality of local devices and a server. Each of the local devices includes a processor. The processor selects a mini-batch from local data. The processor trains a local model using the mini-batch. The processor generates local data information relating to the local data included in the mini-batch and indicating information different from a label. The processor transmits a local model parameter relating to the local model and the local data information to the server. The server includes a processor. The processor calculates an integrated parameter using the local data information acquired from each of the local devices. The processor updates a global model using the integrated parameter and the local model parameter acquired from each of the local devices.

Abstract: A treatment system of embodiments includes an imaging system including one or more radiation sources and a plurality of detectors, a first acquirer, a second acquirer, a first deriver, a second deriver, and a calibrator. The radiation sources radiate radiation to an object in a plurality of different directions. The plurality of detectors detect the radiation at different positions. The first acquirer acquires images based on the radiation. The second acquirer acquires position information of a first imaging device in a three-dimensional space. The first deriver derives the position of the object in the images. The second deriver derives the position of a second imaging device in the three-dimensional space based on the position of the object in the images, the position of the first imaging device, and the like. The calibrator performs calibration of the imaging system based on a derivation result of the second deriver.

Abstract: A medical image processing device includes a first position acquirer, a first converter, a first likelihood image generator, and a learner. The first position acquirer is configured to acquire, as first positions, target positions in plural first images. The first converter is configured to convert the first positions to second positions by expanding movement in a second direction intersecting a first direction based on movement over time of the first positions. The first likelihood image generator is configured to generate a first likelihood image showing a distribution of likelihood of the second positions. The learner is configured to output a model using the plural first images and the first likelihood image as training data, and upon receiving part or all of a transparent image, derives a second likelihood image showing a distribution of likelihood indicating probability of the part or all of the transparent image corresponding to the second positions.

Abstract: According to an embodiment, a radiation therapy device includes an acquirer, a projection position calculator, an element projection image generator, and an element projection image synthesizer. The acquirer acquires a condition of X-ray imaging in a treatment stage and a three-dimensional image of a patient imaged before the treatment stage. The projection position calculator calculates a projection position when each of pixels included in the three-dimensional image is projected onto a two-dimensional X-ray fluoroscopic image generated in the X-ray imaging on the basis of the condition of the X-ray imaging. The element projection image generator generates an element projection image for each pixel when each of the pixels included in the three-dimensional image is projected onto the X-ray fluoroscopic image. The element projection image synthesizer performs a synthesis process for the element projection image for each pixel on the basis of the projection position to generate a reconstructed image.

Abstract: A medical image processing device includes a first image acquiring unit, a second image acquiring unit, a first likelihood distribution calculating unit, a trackability determining unit, and a tracking unit. The first image acquiring unit acquires first images which are transparent images of the patient. The second image acquiring unit acquires second images which are transparent images of the patient generated at a time different from that of the first images. The first likelihood distribution calculating unit calculates a first likelihood distribution indicating a distribution of likelihoods indicating a likeness to the object in the first images. The trackability determining unit determines whether the object is trackable on the basis of the first likelihood distribution. The tracking unit tracks the position of the object in the second images on the basis of the result of determination.

Abstract: According to one embodiment, an analysis apparatus includes processing circuitry. The processing circuitry acquires sensor data from a measurement target, calculates a state value based on the sensor data, sets, based on time-series data of the state value and predetermined criteria, a plurality of noticed sections in the time-series data, performs clustering using the state value regarding each of the noticed sections and generates a clustering result, and generates, based on the clustering result, stress information including characteristic information of each of a plurality of clusters.

Abstract: According to one embodiment, a learning apparatus includes a processor. The processor divides target data into pieces of partial data. The processor inputs the pieces of partial data into a first network model to output a first prediction result and calculates a first confidence indicating a degree of contribution to the first prediction result. The processor inputs the target data into a second network model to output a second prediction result and calculates a second confidence indicating a degree of contribution to the second prediction result. The processor updates a parameter of the first network model, based on the first prediction result, the second prediction result, the first confidence and the second confidence.

Abstract: According to an embodiment, a medical image processing device includes a first image acquirer, a second image acquirer, a direction acquirer, and a movement amount calculator. The first image acquirer acquires a three-dimensional first image obtained by photographing the inside of a body of a patient. The second image acquirer acquires a three-dimensional second image of the inside of the body of the patient imaged at a timing different from that of the first image. The direction acquirer acquires information about an irradiation direction of radiation to the patient in a treatment room. The movement amount calculator outputs a movement amount signal indicating the amount of movement of the second image to be moved to align the position of the patient shown in the second image with the position of the patient shown in the first image based on the path of the radiation set in the first image and the information about the irradiation direction.

Abstract: According to one embodiment, a defect classification apparatus includes a processor. The processor acquires a first design image which is an image based on design data created by design software and relates to a first inspection target, and acquires a first real image which is captured by imaging the first inspection target produced based on the design data. The processor converts the first design image to a reference image represented by using a second real image captured by imaging a second inspection target without a defect. The processor calculates a reliability of the reference image. The processor detects a defect in the first inspection target by comparing the reference image and the first real image and classifies the defect, based on the reliability.

Abstract: A defect inspection device includes at least one memory storing instructions and at least one processor.

Abstract: A medical image processing device of an embodiment includes a comparator and a position determination region determiner. The comparator compares a first image obtained by photographing a patient with a comparative image which is an image used in previous radiation treatment and in which a valid region used in position alignment in the radiation treatment is designated. The position determination region determiner determines a position determination region similar to the valid region included within the first image on the basis of a comparison result of the comparator.

Abstract: According to one embodiment, a defect inspection apparatus includes a storage and a processor. The storage stores dictionary in which a first design image generated by software is associated with a first real image corresponding to the first design image. The processor acquires a second design image generated by the software. The processor searches for a similar first design image similar to the second design image. The processor generates a reference image that is a pseudo real image of a second inspection object, based on the second design data and free of defect, by using the first real image associated with the similar first design image. The first design image includes information of an image area wider than the first real image.

Abstract: A medical image processing device of an embodiment includes a first image acquirer, a second image acquirer, a generator, and a calculator. The first image acquirer acquires a first fluoroscopic image of a patient. The second image acquirer acquires a second fluoroscopic image according to radiation with which the patient is irradiated at a time point different from a time point of acquisition of the first fluoroscopic image from a photography device that detects radiation with a detector and performs an imaging process. The generator generates a reconstructed image obtained by reproducing the second fluoroscopic image from the first fluoroscopic image virtually arranged in a three-dimensional space on the basis of an installation position of the detector in the three-dimensional space. The calculator obtains a suitable position on the first fluoroscopic image in the three-dimensional space on the basis of a degree of similarity between the second fluoroscopic image and the reconstructed image.

Abstract: A medical apparatus includes an acquirer, an associator, and a display controller. The acquirer acquires information indicating a respiratory waveform of an object and acquires fluoroscopic images of the object captured in time series. The associator associates a tracking value which fluctuates according to a respiratory phase of the object, based on the time-series fluoroscopic images. The display controller causes a display to display the respiratory waveform and a waveform of the tracking value in a comparable form.

Abstract: An object positioning apparatus comprising: a radiographic image input interface configured to acquire a radiographic image that is generated by causing a fluoroscopic imaging apparatus to image an object and includes a first region and a second region, the first region depicting an index region for positioning of the object, the second region depicting a non-index region other than the index region; and a positioning processor configured to perform the positioning of the object by performing matching processing between a previously generated reference image and the first region that is specified from the radiographic image based on three-dimensional model information of the non-index region.

Abstract: A treatment system of embodiments includes an imaging system including one or more radiation sources and a plurality of detectors, a first acquirer, a second acquirer, a first deriver, a second deriver, and a calibrator. The radiation sources radiate radiation to an object in a plurality of different directions. The plurality of detectors detect the radiation at different positions. The first acquirer acquires images based on the radiation. The second acquirer acquires position information of a first imaging device in a three-dimensional space. The first deriver derives the position of the object in the images. The second deriver derives the position of a second imaging device in the three-dimensional space based on the position of the object in the images, the position of the first imaging device, and the like. The calibrator performs calibration of the imaging system based on a derivation result of the second deriver.

Abstract: A medical apparatus according to an embodiment includes an acquirer and a selector. The acquirer is configured to acquire fluoroscopic images of an object captured in time series. The selector is configured to select reference images which include fluoroscopic images corresponding to a maximum exhalation position and a maximum inhalation position of the object from the plurality of fluoroscopic images acquired by the acquirer.

Abstract: A medical apparatus according to an embodiment includes an acquirer, a corrector, an identifier, and an output controller. The acquirer is configured to acquire a fluoroscopic image of an object from an imager. The corrector is configured to correct an image of one or more predetermined regions used for identifying a target position of the object in the fluoroscopic image based on one or more correction values but does not correct an image of at least a part of a region out of the predetermined region in the fluoroscopic image. The identifier is configured to identify the target position based on an image corrected by the corrector. The output controller is configured to output an irradiation permission signal to a therapeutic device which irradiates the object with a therapeutic beam based on the target position identified by the identifier.