A fundus imaging apparatus includes an imaging optical system that irradiates a fundus of a subject eye with light through an objective lens system, and enables to capture a fundus image of the subject eye based on return light from the subject eye, and a diopter correction unit that includes an optical element disposed on an optical path of the imaging optical system and a drive unit driving the optical element, and performs a diopter correction with a diopter value corresponding to a drive amount of the optical element. A drive range of the optical element in the diopter correction unit is set to avoid a specific range being a range in which an artifact caused by reflection light in the objective lens system is maximized.

An ophthalmological image processing apparatus acquires a plurality of images of a subject eye photographed in a scanning-type imaging optical system, sets any one of the plurality of images as a template, sets corresponding points or corresponding regions between an image of the subject eye and the template at a plurality of positions of each of the image of the subject eye and the template, calculates a movement amount of each of the corresponding points or each of the corresponding regions, and corrects a distortion of the image of the subject eye with respect to the template based on the movement amount of each of the corresponding points or each of the corresponding regions.

The invention relates to an assembly (10) comprising an OCT device (20) for scanning an object region volume (22) arranged in an object region (18) using an OCT scanning beam (21), an object (24) with a section, which can be arranged in the object region (18) and which can be located in the object region volume (22) by means of the OCT device (20), in the object region volume (22), and a calculating unit (60) which is connected to the OCT device (20) and contains a computer program for ascertaining a 3D reconstruction of the object region volume (22) and for ascertaining the position of the section of the object (24) in the object region volume (22) by processing OCT scanning information obtained by scanning the object region volume (22) using the OCT device (20). According to the invention, the computer program has a calculation routine for ascertaining a target area (90) in the 3D reconstruction of the object region volume (22), said calculation routine determining a reference variable for the object (24) relative to the target area (90). The object (24) is designed as a surgical instrument which has a capillary with an opening for discharging a medium. The calculation routine of the computer program is used to ascertain an actual value of the volume of the medium discharged through the opening of the capillary in the target area by comparing data of the target area in the 3D reconstruction of the object region volume (22) and/or by comparing scanning information of the target area obtained by scanning the object region volume (22) using the OCT device (20) prior to and while discharging the medium. The invention also relates to a computer program and to a method for determining the volume of a medium discharged in an object region (18) through an opening by means of a surgical instrument with a capillary.

An optical relay comprises a first scan mirror configured to receive an input optical beam, and to reflect the input optical beam as a first intermediate optical beam; a telecentric mirror configured to receive the first intermediate optical beam, and to reflect the first intermediate optical beam as a second intermediate optical beam; a second scan mirror configured to receive the second intermediate optical beam, and to reflect the second intermediate optical beam as an output optical beam; and a lens system disposed between the telecentric mirror and the first and second scan mirrors, such that the first intermediate optical beam and the second intermediate optical beam pass through the lens system. The optical relay may be a component of an optical system which further includes an optical engine.

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.

The present disclosure describes a deep learning algorithm with the ability to provide a high-performance classifier to predict either the presence of geographic atrophy (GA), or the likelihood of progression from intermediate age-related macular degeneration to GA. The system can also be used for broader applications outside of eye disease.

Apparatus and methods are presented for spectral domain optical imaging, in particular for single shot 3-D spectral domain imaging of the retina of the human eye. In certain embodiments one or more 3-D images across elongated areas of an object are acquired, with scanning perpendicular to the long axis of the elongated areas for imaging extended volumes of the object. In preferred embodiments the captured light is sampled in the Fourier plane, in a dimension substantially perpendicular to the long axis, with a cylindrical lenslet array, while in other embodiments the captured light is sampled in the image plane. Apparatus and methods are also presented for hyperspectral imaging of the retina, with the illuminating beams preferably angled to suppress interference from corneal reflections. Apparatus and methods are also presented for multi-wavelength wavefront sensing, with simultaneous capture of light in two or more paths with different delays.

The invention relates to a computer-implemented method and a corresponding system for a machine-learning-supported determining of refractive power for a measure for correcting the eyesight of a patient. The method involves providing a scan result of an eye, wherein the scan result represents an image of an anatomical structure of the eye. The method also involves supplying the scan result as input data to a first machine-learning system in the form of a convolutional neural network, and using output values of the first machine-learning system as input data for a second machine-learning system in the form of a multi-layer perceptron, and a target refraction value for the second machine-learning system is used as an additional input value for the second machine-learning system. Finally, the method involves determining parameters for the measure for correcting the eyesight of a patient via an immediate and direct cooperation of the first machine-learning system and the second machine-learning system.

Methods and apparatus are presented for obtaining high-resolution 3-D images of a sample over a range of wavelengths, optionally with polarisation-sensitive detection. In preferred embodiments a spectral domain OCT apparatus is used to sample the complex field of light reflected or scattered from a sample, providing full range imaging. In certain embodiments structured illumination is utilised to provide enhanced lateral resolution. In certain embodiments the resolution or depth of field of images is enhanced by digital refocusing or digital correction of aberrations in the sample. Individual sample volumes are imaged using single shot techniques, and larger volumes can be imaged by stitching together images of adjacent volumes. In preferred embodiments a 2-D lenslet array is used to sample the reflected or scattered light in the Fourier plane or the image plane, with the lenslet array suitably angled with respect to the dispersive axis of a wavelength dispersive element such that the resulting beamlets are dispersed onto unique sets of pixels of a 2-D sensor array.

An OCT device includes an OCT optical system and a controller that also serves as an image processor. The controller acquires the OCT data of the fundus by processing the spectral interference signal output from the OCT optical system. In addition, the controller adjusts the position of the high accuracy region, which is the depth region where relatively high accuracy OCT data is obtained, by controlling the OCT optical system in accordance with the curvature level of the fundus image in the photographing range of the OCT data. This makes it possible to acquire good OCT data regardless of the curvature level of the fundus.