A method for fitting OK lenses to a patient comprising the steps of: applying a corneal topography apparatus to a patient to capture baseline and post wear maps of a cornea of the patient in a computer to thereby derive a difference map; processing the difference map to fit Zernike polynomials thereto wherein weights of said fitted polynomials comprise features of a test feature vector for the difference map; applying the test feature vector to a classification machine trained to classify the difference map as one of a number of predetermined classes; and subsequently treating the patient taking into account the classification machine's classification.

An ophthalmologic processing apparatus according to embodiments acquires data of a fundus of a subject's eye optically. The ophthalmologic apparatus includes a fixation system, an image acquisition unit, a specifying unit, and a determination unit. The fixation system is configured to project fixation light onto an eye of a subject. The image acquisition unit is configured to acquire an image of the fundus of the subject's eye in a state where the fixation light is projected by the fixation system. The specifying unit is configured to analyze the image acquired by the image acquisition unit to specify an image region corresponding to a predetermined site of the fundus. The determination unit is configured to determine whether or not the image region specified by the specifying unit is included within a predetermined range in the image acquired by the image acquisition unit.

A line-of-sight measurement device includes: an imaging unit that images a face of a subject; a light illumination unit that illuminates light to an eye of the subject; a camera coordinate system eyeball center coordinate calculation unit that estimates coordinates of an eyeball center, from a face image imaged by the imaging unit; a pupil center calculation unit that estimates coordinates of an apparent pupil center, from a pupil center position on the face image; an eyeball position orientation estimation unit that calculates an optical axis vector toward the pupil center from the eyeball center on the basis of the coordinates of the eyeball center and the apparent pupil center; a corneal reflection image calculation unit that obtains coordinates of a corneal reflection image on the basis of the coordinates of the eyeball center, the optical axis vector, and a predetermined eyeball model; and an image coordinate calculation unit that estimates image coordinates of a corneal reflection image on the face image, from the coordinates of the corneal reflection image.

An image processor performs a histogram acquisition step of acquiring a histogram representing a distribution of gradation values of pixels in a fundus color image captured by irradiating a fundus with a plurality of beams of single-color light having different wavelengths, the histogram being acquired for each channel corresponding to each beam of single-color light, a histogram correction step of acquiring a corrected histogram by correcting the histogram of each channel acquired in the histogram acquisition step, of which a target pattern is set for each channel in advance, so as to fit to the corresponding target pattern, and a color tone corrected image generation step of generating a color tone corrected image, in which a distribution of gradation values for each channel is represented by the corrected histogram, based on the corrected histogram of each channel.

Retinal imaging systems and methods are described. In an embodiment, the retinal imaging system includes an eyepiece lens assembly; an image sensor adapted to acquire a retinal image of an eye through the eyepiece lens assembly; a dynamic fixation target optically coupled to the eyepiece lens assembly such that the dynamic fixation target is viewable through the eyepiece lens assembly; and a controller communicatively coupled to the image sensor and the dynamic fixation target. In an embodiment, the dynamic fixation target includes a display where an image generated by the display is controlled by a position of a user's eye relative to the eyepiece lens assembly.

Provided herein is a corneal topography system that utilizes a prism placed in optical alignment between the pattern image generator, such as a Placido disk, and the eye. The corneal topography system may be a prismatic triangulating corneal topography system that utilizes light rays of angle θ at the edge of the prism not passing through the prism, light rays that deviate from angle θ passing through the prism and light rays of angle a calculated from the reflection image to determine the corneal reflection point on the corneal surface. Also provided is a method for mapping a corneal surface of an eye of a subject utilizing an optical prism to produce a reflection image from a corneal surface reflection point on the corneal surface of the eye.

An eye-gaze detecting device includes an image data acquisition unit configured to acquire image data of an eyeball of a test subject irradiated with detection light; a position detection unit configured to detect, from the image data, position data of pupil center of the eyeball and position data of corneal reflection center; a pupil diameter calculation unit configured to calculate a pupil diameter of the test subject from the image data; a curvature center calculation unit configured to calculate a corneal curvature radius corresponding to the pupil diameter, and obtain position data of corneal curvature center based on the position data of the corneal reflection center and the corneal curvature radius; and a point-of-gaze detection unit configured to calculate, based on the position data of the pupil center and corneal curvature center, position data of point of gaze of the test subject on a plane including a display unit.

Embodiments disclose systems and methods that aid in screening, diagnosis and/or monitoring of medical conditions. The systems and methods may allow, for example, for automated identification and localization of lesions and other anatomical structures from medical data obtained from medical imaging devices, computation of image-based biomarkers including quantification of dynamics of lesions, and/or integration with telemedicine services, programs, or software.

A device and a method for determining a change in the visual comfort of a user, the device including at least one light source for stimulating at least one eye of the user, a sensing circuit facing at least one eye area of the user when the device is worn by the user, the sensing circuit being configured to remotely acquire at least one signal representative of at least one characteristic of said at least one eye area, and a controller configured to determine a change in the visual comfort of the user depending on a variation of said at least one signal acquired by the sensing circuitry.

A computer implemented system and method for determining and analysing ocular refractive error of an eye. The method determines a set of sample biometric factors for a reference sample of eyes from a set of reference sample physical characteristics. Physical characteristics of a patient’s eye are measured such that the type of measured patient physical characteristics include some or all of the reference sample characteristic types. Patient biometric factors are then calculated based on the measured and inherent patient physical characteristics and compared with the sample biometric factors to determine the effect of one or more parameters on the ocular refractive error of an eye. The method may calculate the difference between the refractive contribution of the axial length, cornea and internal optics in the patient’s eye and the separate contribution from those factors in the sample physical characteristics.