Fujifilm Corporation

Fuji Photo Film Company, Limited

Fujifilm Medical Systems U.s.a., Inc.

Sadato Akahori

Yasunori Ohta

Noriaki Ida

Kazuharu Ueta

Kensuke Terakawa

Eiichi Kanagawa

Atsushi Fukuda

Takuya Fuchigami

Jun Enomoto

Yoshiro Kitamura

Wataru Ito

Yuanzhong Li

Yuichi Teramura

Tomoyoshi Nishimura

Yoshitaka Yamaguchi

Hirofumi Sawada

Eiichi Kito

Tomoyuki Takahashi

Keigo Nakamura

Takahiro Kawamura

Masahiko Yamada

Mizuki Takei

Karin Kuroiwa

Keiji Sugihara

Kouji Yokouchi

Yoshikatsu Morishima

An image alignment apparatus includes at least one processor, and the processor derives, for each of first and second three-dimensional images each including a plurality of tomographic images and a common structure, first and second three-dimensional coordinate information that define an end part of the structure in a direction intersecting the tomographic image. The processor aligns the first three-dimensional image and the second three-dimensional image by using the first and second three-dimensional coordinate information to align the common structure included in each of the first three-dimensional image and the second three-dimensional image at least in the direction intersecting the tomographic image.

Image alignment apparatus, method, and program

An image processing apparatus includes at least one processor, and the processor derives three-dimensional coordinate information that defines a position of a structure in a tomographic plane from a tomographic image including the structure, and that defines a position of an end part of the structure outside the tomographic plane in a direction intersecting the tomographic image.

Image processing apparatus, method and program, learning apparatus, method and program, and derivation model

A learning image generation device including: a supervised data acquisition unit that acquires supervised data including a learning image and a correct learning image in which a correct region is defined in the learning image as a pair; and a variation learning image generation unit that generates a variation learning image in which a pixel value of a pixel belonging to the correct region is varied within a limitation range of an allowable pixel value of the pixel belonging to the correct region in the learning image.

Learning image generation device, learning image generation method, learning image generation program, learning method, learning device, and learning program

A learning image generation device includes an image acquisition unit that acquires a learning image, and a variation learning image generation unit that generates a variation learning image by adding a variation in which an output of a model deviates from a target value to a pixel value of at least one pixel that constitutes the learning image in a case in which the learning image acquired by the image acquisition unit is input to the model.

Provided are a disease region extraction apparatus, a disease region extraction method, and a disease region extraction program that can extract an infarction region even in an image in which it is difficult to prepare a large amount of data indicating a correct infarction region. A disease region extraction apparatus includes: an image acquisition unit that acquires a first image obtained by capturing an image of a subject that has developed a disease; an estimated image derivation unit that estimates a second image, whose type is different from the type of the first image, from the first image to derive an estimated image; and a disease region extraction unit that extracts a disease region from the estimated image.

Disease region extraction apparatus, disease region extraction method, and disease region extraction program

An analysis result acquisition unit acquires an analysis result of a medical image. A medical information acquisition unit acquires medical information different from the medical image. A priority deriving unit derives a priority of the medical image based on the analysis result and the medical information.

Priority judgement device, method, and program

A discriminator includes a common learning unit and a plurality of learning units that are connected to an output unit of the common learning unit. The discriminator is trained, using a plurality of data sets of a medical image and an image data of a first disease region, such that information indicating the first disease region is output from a first learning unit in a case in which the medical image is input to the common learning unit. The discriminator is trained, using a plurality of data sets of a medical image and an image data of a second disease region having at least one of a medical causal relationship or an anatomic causal relationship with the first disease, such that information indicating the second disease region is output from a second learning unit in a case in which the medical image is input to the common learning unit.

Apparatus, method, and program for training discriminator discriminating disease region, discriminator discriminating disease region, disease region discrimination apparatus, and disease region discrimination program

A discriminator includes a common learning unit and a plurality of learning units that are connected to an output unit of the common learning unit. The discriminator is trained, using a plurality of data sets of a first image obtained by capturing an image of a subject that has developed a disease and an image data of a disease region in the first image, such that information indicating the disease region is output from a first learning unit in a case in which the first image is input to the common learning unit. In addition, the discriminator is trained, using a plurality of data sets of an image set obtained by registration between the first image and a second image whose type is different from the type of the first image, such that an estimated image of the second image is output from an output unit of a second learning unit.

Reception means receives examination data including a plurality of examination images. Association means associates an examination image similar to each sample image included in the layout with a sample image using a similarity between each sample image included in a layout and each of a plurality of examination images included in examination data. Display means displays the examination image associated with the sample image at an arrangement position where the sample image is arranged in the layout.

Automatic layout apparatus, automatic layout method, and automatic layout program

An image diagnosis support apparatus includes: an acquisition unit that acquires a plurality of first image data groups and a plurality of second image data groups to be subjected to comparative interpretation; an association unit that associates each of the plurality of first image data groups and each of the plurality of second image data groups with each other based on a degree of similarity between the image data groups; an image extraction unit that extracts a corresponding image corresponding to at least one target image of the first image data group from a second image data group among the plurality of second image data groups associated with a first image data group among the plurality of first image data groups; and a display controller that displays a set of images of the target image and the corresponding image on a display unit in a contrastable layout.

Image diagnosis support apparatus, image diagnosis support method, and image diagnosis support program

Similarity acquisition means calculates a similarity in each combination of an examination cross-sectional image and a reference cross-sectional image between examination volume data and reference volume data. Adjustment value acquisition means acquires an adjustment value of the similarity based on a relationship between the cross-sectional positions of examination cross-sectional images in two combinations and a relationship between the cross-sectional positions of reference cross-sectional images in the two combinations. Association means associates the examination cross-sectional image and the reference cross-sectional image with each other based on a sum of all the similarities and all the adjustment values.

Registration apparatus, registration method, and registration program

There is provide a medical image processing apparatus, a medical image processing method, and a medical image processing program that can accurately specify at least either vertebral bodies or intervertebral discs included in the vertebra even if parts of the vertebral bodies and the intervertebral discs are deformed. A candidate detection unit detects intervertebral disc candidates and vertebral body candidates from a medical image, and a centerline detection unit detects a spine centerline. A distribution generation unit generates the distribution of a feature amount indicating the intervertebral disc likeness and a feature amount indicating the vertebral body likeness on the spine centerline. A specification unit specifies at least either the intervertebral discs or the vertebral bodies included in the medical image based on the distribution.

Medical image processing apparatus, medical image processing method, and medical image processing program

A medical image processing apparatus includes a medical image data obtaining unit for obtaining medical image data containing an image of a heart, and a region extraction processing unit for extracting a left ventricular region of the heart in the medical image data obtained by the medical image data obtaining unit, and, based on an extraction result of the left ventricular region, performing region extraction processing for extracting at least one of a right ventricular region, a left atrium region, and a right atrium region of the heart.

Medical image processing apparatus, method, and program

There are provided a feature point extraction unit that extracts an anatomical feature point included in a medical image based on the medical image and a standardization conditions acquisition unit that acquires standardization conditions of pixel values of the medical image based on some pixel values around the anatomical feature point among the pixel values of the medical image.

Medical image processing device, operation method therefor, and medical image processing program

An X-ray exposure control device comprises: an X-ray detection element including a plurality of pixels for dose detection each detecting a dose during X-ray radiation; a region setting unit configured to set a use pixel region including pixels for use in dose detection from the plurality of pixels for dose detection during the X-ray radiation; a signal generating unit configured to generate a stop signal for stopping the X-ray radiation from an X-ray source according to the dose detected by each of the pixels for use in the dose detection within the use pixel region set by the region setting unit; and a transmission unit configured to transmit to the X-ray source the stop signal to stop the X-ray radiation as generated by the signal generating unit.

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Kanagawa-ken, Japan

Sadato Akahori