Abstract: An ophthalmic information processing apparatus includes a feature amount extractor and a classifier. The feature amount extractor is configured to extract a feature amount of each of two or more images different from each other of a subject’s eye. The classifier is configured to output two or more confidence score information for estimating classification result of a pathological condition of a disease of the subject’s eye, based on the feature amounts of each of the two or more images extracted by the feature amount extractor and one or more background data representing a state of the subject or a state of the subject’s eye.

Abstract: An ophthalmic information processing apparatus includes an acquisition unit and a disease estimation unit. The acquisition unit is configured to acquire a plurality of images with different cross-sectional orientations from each other of a subject’s eye. The disease estimation unit is configured to output estimation information for estimating whether or not the subject’s eye is a glaucoma eye from the images, using a plurality of learned models obtained by performing machine learning for each type of the images.

Abstract: An ophthalmic information processing apparatus includes a determiner and a detector. The determiner is configured to determine a presence or absence of a disc hemorrhage for a front image of a fundus of a subject's eye, using a disc hemorrhage determination model obtained by performing machine learning using a plurality of fundus images labeled with labels indicating the presence or absence of a disc hemorrhage as first teaching data. The detector is configured to detect a disc hemorrhage region depicted in the front image that is determined to have the disc hemorrhage, using a disc hemorrhage region detection model obtained by performing machine learning using a plurality of pairs of image groups as second teaching data, each pair having a front image of a fundus and a disc hemorrhage region image representing a disc hemorrhage region depicted in the front image.

Abstract: An ophthalmic information processing system according to an embodiment includes a receiver and a processor. The receiver receives morphological data of an eye fundus of a subject. In addition, the receiver receives background data of the subject. The processor executes optic nerve head shape classification based on the morphological data and the background data received by the receiver.

Abstract: A fundus analysis apparatus includes a storage, an area setting unit, and a morphological information generating unit. The storage is configured to store OCT information acquired by applying optical coherence tomography to the fundus of an eye. The area setting unit is configured to set a front area corresponding to a front surface of the lamina cribrosa and a rear area corresponding to a rear surface of the lamina cribrosa in the OCT information. The morphological information generating unit is configured to generate morphological information indicating the morphology of the lamina cribrosa based on at least the front area and the rear area.

Abstract: An ophthalmic information processing system according to an embodiment includes a receiver and a processor. The receiver receives morphological data of an eye fundus of a subject. In addition, the receiver receives background data of the subject. The processor executes optic nerve head shape classification based on the morphological data and the background data received by the receiver.

Abstract: A fundus analysis apparatus includes a storage, an area setting unit, and a morphological information generating unit. The storage is configured to store OCT information acquired by applying optical coherence tomography to the fundus of an eye. The area setting unit is configured to set a front area corresponding to a front surface of the lamina cribrosa and a rear area corresponding to a rear surface of the lamina cribrosa in the OCT information. The morphological information generating unit is configured to generate morphological information indicating the morphology of the lamina cribrosa based on at least the front area and the rear area.