Provided is an image processing device, an image processing method, or a program that can obtain an image for lens opacity determination that facilitates opacity determination for a lens. An image processing device acquires a transillumination image of a lens captured by a capturing device, and performs a flat correction process to reduce illumination unevenness in the transillumination image. In the flat correction process, an average filter is generated on the basis of an original image of the transillumination image, the original image is divided by the average filter, and values after division are multiplied by an average luminance of the original image. The transillumination image after the flat correction process is converted to a binarized image composed of white and black. Determination for lens opacity is performed on the basis of the binarized image.

A system and method for ophthalmic surgery in which a light field camera is used to capture a digital image of the surgical field including the eye. The digital image is used to create image information and directional information, which is then used to from a three dimensional (3D) image with motion parallax.

The present invention relates to systems and methods of monitoring and encouraging activity in infants, and more specifically, the present invention relates to systems and methods of interactively monitoring and encouraging infants to exercise their neck and back muscles. The present invention further comprises method of treating torticollis in infants.

A method and system for diagnosis of a cataract, using deep learning, wherein deep learning predicts the degree of progression of a cataract from slit lamp examination result images and retroillumination examination result images and the severity is assessed on the basis of the prediction, whereby a therapeutic plan is established. A method for diagnosis of a cataract, using deep learning may include: receiving slit lamp examination result images and health diagnosis results of a subject; inputting the examination result images into a deep learning prediction model to predict a degree of progression of a cataract in the lens nucleus and determining whether the subject is affected by a cataract; assessing the severity of the cataract on the basis of the degree of progression of the cataract in the lens nucleus; and using the severity of the cataract or the health examination result to determine a cataract treatment.

An optoelectronic apparatus and method is provided. The application of which provides a quantitative index of cataract opacity in the human eye to help the clinical practitioner screen patients for referral for cataract lens replacement surgery. The invention includes at least one adjustable intensity optical reference light source selected from the group consisting of a green light source and a red-light source. The invention also includes at least one fixed intensity cataract absorption light source, selected from the group consisting of a blue light source, an indigo light source, and a violet light source.

The present invention discloses a technique for alerting on vision impairment. The system comprises a processing unit configured and operable for receiving scene data being indicative of a scene of at least one consumer in an environment, identifying in the scene data a certain consumer, identifying an event being indicative of a behavioral compensation for vision impairment, and, upon identification of such an event, sending a notification relating to the vision impairment.

A portable digital imaging device, which utilizes the advanced features of wireless data transmission and high computing power of mobile computing devices in junction with the use miniature cameras and solid state lighting technology, is proposed as the next generation of medical imaging devices, in particular in ophthalmic imaging applications.

An ocular fundus image processing device acquires a first image generated by irradiating an ocular fundus of a subject with excitation light of a blue wavelength and a second image generated by irradiating the ocular fundus with excitation light of a green wavelength, generates three trained models for predicting a correction factor for calculating a quantity of macular pigment of the subject from input images including the first image and the second image through training using three different initial values, predicts three correction factors by inputting the input images including the first image and the second image to the three trained models, calculates a statistical value of the three correction factors and derives the statistical value as the correction factor of the subject, and calculates a quantity of macular pigment of the subject on the basis of the first image and the correction factor of the subject.

An examination system (100) includes a measurement unit (2) that is movable to change an angle relative to an eyeball (200) of a subject and rotatably moved around an eye axis of the eyeball (200) as a rotation axis, an illumination unit (3) that is mounted on the measurement unit (2) to irradiate the eyeball (200), a first camera unit (4L) that is mounted on the measurement unit (2) to image the eyeball (200), and a second camera unit (4R) that is mounted on the measurement unit (2) to image the eyeball (200), in which the first camera unit (4L) and the second camera unit (4R) are independently movable on the measurement unit (2) to change angles relative to the eyeball (200).

An estimation system, method and program for estimating the age of an eye to be examined. The estimation system includes an acquisition module configured to acquire a measurement value of an attribute of an eye to be examined, the attribute being at least one of a plurality of characteristics of an anterior segment and a plurality of dimension values of the eye to be examined; and a determination module configured to determine an estimated age of the eye to be examined on the basis of the measurement value and correspondence information indicating a correspondence between a value of the attribute and an age of an eyeball.