Fujifilm Corporation

Takuya Fuchigami

Sadato Akahori

Keigo Nakamura

Mizuki Takei

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 division unit divides an axisymmetric structure in a medical image including the structure into a plurality of predetermined regions. A reference line derivation unit derives a reference line of the structure on the basis of the plurality of divided regions.

Medical image processing apparatus, method, and program

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

The conversion apparatus includes a selection section that selects a category of a term used for a report of a medical image; and a conversion section that converts an input term of the report to the term of the category selected by the selection section, with reference to a conversion table in which terms of plural types of the categories are associated with each other.

Conversion apparatus, conversion method, and 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 support program is a program for supporting creation of an interpretation report including a medical image obtained by examining a patient and a region of interest to focus on in the medical image. The support program causes a computer to function as: a reading unit that reads a plurality of interpretation reports created by a plurality of examinations on the same part of the same patient; a difference detection unit that sets one of the plurality of interpretation reports as a detection target interpretation report and sets the others as comparison target interpretation reports, compares regions of interest of the detection target interpretation report and the comparison target interpretation reports, and detects a region of interest, which is present in the comparison target interpretation reports but is not present in the detection target interpretation report, as a difference region; and a notification screen distribution unit that, in a case where the difference region is detected, notifies that the difference region has been detected.

Interpretation support apparatus and non-transitory computer readable medium

An analysis unit analyzes a medical image and acquires an analysis result. An interpretation report creation unit creates an interpretation report on a disease based on the analysis result. A display control unit displays the medical image and the interpretation report on a display. In response to an instruction to modify one of a disease region in the medical image and a description of the disease region in the interpretation report, a modification unit modifies the other one of the disease region in the medical image and the description of the disease region in the interpretation report.

Medical image display device, method, and program

An image acquisition unit acquires a CT image and one or more MRI images of the brain of a subject that has developed a cerebral infarction. An infarction region extraction unit extracts an infarction region corresponding to the time elapsed since the development from the MRI image. A registration unit performs registration between the CT image and the MRI image. An infarction region specification unit specifies the infarction region corresponding to the time elapsed since the development in the CT image on the basis of the result of the registration. A learning unit learns a discriminator which discriminates an infarction region corresponding to the time elapsed since the development in the CT image to be discriminated, using the infarction region corresponding to the time elapsed since the development, which has been specified in the CT image, as teacher data.

Apparatus, method, and program for learning discriminator discriminating infarction region, discriminator for discriminating infarction region, and apparatus, method, and program for discriminating infarction region

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Tokyo, Japan

Takuya Fuchigami