Abstract: A medical image processing apparatus includes: an obtaining unit configured to obtain a first image that is a motion contrast en-face image of an eye to be examined; and an image quality improving unit configured to generate a second image with at least one of lower noise and higher contrast than the obtained first image using the obtained first image as input data that is input into an image quality improving engine, wherein the image quality improving engine includes a machine learning engine that has been obtained by using training data including a second image with at least one of lower noise and higher contrast than a first image that is a motion contrast en-face image of an eye to be examined.

Abstract: An image processing apparatus includes display control means for displaying, on display means, a blend image obtained by performing blend processing at a variable transmissivity in accordance with an instruction of an operator using an optical coherence tomography (OCT) image and an OCT angiography (OCTA) image of mutually corresponding regions in a subject that are acquired by an OCT, setting means for setting a region of interest in the displayed blend image, and execution means for executing processing on the set region of interest in at least one image of the OCT image and the OCTA image.

Abstract: A medical image processing apparatus includes: an obtaining unit configured to obtain a first image that is a motion contrast en-face image of an eye to be examined; and an image quality improving unit configured to generate a second image with at least one of lower noise and higher contrast than the obtained first image using the obtained first image as input data that is input into an image quality improving engine, wherein the image quality improving engine includes a machine learning engine that has been obtained by using training data including a second image with at least one of lower noise and higher contrast than a first image that is a motion contrast en-face image of an eye to be examined.

Abstract: An image processing apparatus includes display control means for displaying, on display means, a blend image obtained by performing blend processing at a variable transmissivity in accordance with an instruction of an operator using an optical coherence tomography (OCT) image and an OCT angiography (OCTA) image of mutually corresponding regions in a subject that are acquired by an OCT, setting means for setting a region of interest in the displayed blend image, and execution means for executing processing on the set region of interest in at least one image of the OCT image and the OCTA image.

Abstract: The optical coherence tomography apparatus is an optical coherence tomography apparatus that obtains a tomographic image of an eye to be examined by using combined light obtained by combining (a) return light from the eye to be examined irradiated with measurement light and (b) reference light, the optical coherence tomography apparatus including an optical path length difference changing unit arranged to change an optical path length difference between the measurement light and the reference light, a driving unit arranged to drive the optical path length difference changing unit, a determining unit configured to determine, using a learned model, a driving amount of the driving unit from the obtained tomographic image, and a controlling unit configured to control the driving unit using the determined driving amount.

Abstract: A medical image processing apparatus including an obtaining unit configured to obtain a plurality of tomographic images obtained by radially scanning measuring light on an eye to be examined, and corresponding to a plurality of locations of the eye to be examined, respectively, and an imaging parameter corresponding to each tomographic image, a modifying unit configured to modify a shape of a tomographic image corresponding to the imaging parameter by using the imaging parameter, and an aligning unit configured to align a plurality of shape-modified tomographic images with each other.

Abstract: The optical coherence tomography apparatus is an optical coherence tomography apparatus that obtains a tomographic image of an eye to be examined by using combined light obtained by combining (a) return light from the eye to be examined irradiated with measurement light and (b) reference light, the optical coherence tomography apparatus including an optical path length difference changing unit arranged to change an optical path length difference between the measurement light and the reference light, a driving unit arranged to drive the optical path length difference changing unit, a determining unit configured to determine, using a learned model, a driving amount of the driving unit from the obtained tomographic image, and a controlling unit configured to control the driving unit using the determined driving amount.

Abstract: An apparatus includes an obtaining unit configured to obtain, using an optical coherence tomography, an analysis map for a disk and an analysis map for a macular area, which are analysis results of three-dimensional data obtained by capturing an image of a region of a fundus of a subject's eye that includes the disk and the macular area, and a control unit configured to cause a display unit to display side by side a two-dimensional image of the region including the disk and the macular area, the analysis map for the optic disk, and the analysis map for the macular area.

Abstract: An image processing apparatus includes display control means for displaying, on display means, a blend image obtained by performing blend processing at a variable transmissivity in accordance with an instruction of an operator using an optical coherence tomography (OCT) image and an OCT angiography (OCTA) image of mutually corresponding regions in a subject that are acquired by an OCT, setting means for setting a region of interest in the displayed blend image, and execution means for executing processing on the set region of interest in at least one image of the OCT image and the OCTA image.

Abstract: A medical image processing apparatus includes: an obtaining unit configured to obtain a first image that is a medical image of a predetermined site of a subject; an image quality improving unit configured to generate, from the first image, a second image in which image quality is improved compared to the first image, using an image quality improving engine including a machine learning engine; and a display controlling unit configured to cause a composite image obtained by combining the first image and the second image according to a ratio obtained using information relating to at least a partial region in at least one of the first image and the second image to be displayed on a display unit.

Abstract: A medical image processing apparatus includes: an obtaining unit configured to obtain a first image that is a motion contrast en-face image of an eye to be examined; and an image quality improving unit configured to generate a second image with at least one of lower noise and higher contrast than the obtained first image using the obtained first image as input data that is input into an image quality improving engine, wherein the image quality improving engine includes a machine learning engine that has been obtained by using training data including a second image with at least one of lower noise and higher contrast than a first image that is a motion contrast en-face image of an eye to be examined.

Abstract: An image processing apparatus includes: an obtaining unit configured to obtain a first image of an eye to be examined; an image quality improving unit configured to generate a second image with at least one of lower noise and higher contrast than the obtained first image using the obtained first image as an input data of a learned model, wherein the learned model has been obtained by using training data including a second image with at least one of lower noise and higher contrast than a first image of an eye to be examined; and a display controlling unit configured to cause the obtained first image and the generated second image to be switched, juxtaposed or superimposed and displayed on a display unit.

Abstract: A medical image processing apparatus including an obtaining unit configured to obtain a tomographic image of an eye to be examined, and a first processing unit configured to perform first detection processing for detecting at least one layer of a plurality of layers in the obtained tomographic image, by using the obtained tomographic image as an input data of a learned model, wherein the learned model has been obtained by using training data including data indicating at least one layer of a plurality of layers in a tomographic image of an eye to be examined.

Abstract: An image processing apparatus including an identification unit configured to identify a lamina cribrosa region by analyzing tomographic image data on an eye to be inspected, a generation unit configured to generate a luminance en face image and a motion contrast en face image of the eye to be inspected by using information on the identified lamina cribrosa region, and a display control unit configured to cause a display unit to display at least one of the luminance en face image and the motion contrast en face image with the information on the identified lamina cribrosa region superimposed on the displayed image.

Abstract: A medical image processing apparatus includes: an obtaining unit configured to obtain a first image that is a medical image of a predetermined site of a subject; an image quality improving unit configured to generate, from the first image, a second image in which the image quality is improved compared to the first image by using an image quality improving engine that includes a machine learning engine; and a display controlling unit configured to cause a display unit to display a composite image obtained by combining the first image and the second image according to a ratio obtained using information relating to at least a partial region of the first image.

Abstract: An image processing apparatus includes an acquisition unit configured to acquire a tomographic image of at least a retina and a vitreous body of a subject's eye, and a detection unit configured to detect, based on an intensity value of the tomographic image, an outer edge of the vitreous body in a region located on a vitreous body side of a region regarding the retina in the tomographic image.

Abstract: An image processing system includes: an analysis unit configured to obtain information indicating a degree of curvature of a retina from a tomographic image of an eye to be examined; and an obtaining unit configured to obtain a category of the eye to be examined based on an analysis result.

Abstract: An apparatus includes: an acquisition unit configured to acquire pieces of three-dimensional data of a subject eye obtained at different times, the three-dimensional data including pieces of two-dimensional data obtained at different positions; a first planar alignment unit configured to perform first planar alignment including alignment between the pieces of three-dimensional data in a plane orthogonal to a depth direction of the subject eye; a first depth alignment unit configured to perform first depth alignment including alignment between pieces of two-dimensional data in at least one piece of three-dimensional data among the pieces of three-dimensional data and further including alignment between the pieces of three-dimensional data in the depth direction; and a generation unit configured to generate interpolation data of at least one piece of three-dimensional data among the pieces of three-dimensional data by using a result of the first planar alignment and a result of the first depth alignment.

Abstract: A first area and a second area are set for a first two-dimensional tomographic image where the first area and the second area overlap each other in a partial area in a horizontal direction of the first two-dimensional tomographic image. A positional deviation amount between the first two-dimensional tomographic image and a second two-dimensional tomographic image is obtained in each of the first area and the second area. A moving amount of the second two-dimensional tomographic image is determined with respect to the first two-dimensional tomographic image in an area where the first area and the second area overlap based on the positional deviation amount in the first area and the positional deviation amount the second area. Alignments are performed on the first two-dimensional tomographic image and the second two-dimensional tomographic image in an area where the first area and the second area overlap based on the moving amount.

Abstract: An image processing apparatus includes first alignment means configured to perform an alignment in a horizontal direction on a plurality of two-dimensional tomographic images based on measurement light controlled to scan an identical position of an eye according to a first method, and second alignment means configured to perform an alignment in a depth direction on the plurality of two-dimensional tomographic images according to a second method that is different from the first method.