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72 results about "Corneal topography" patented technology

Corneal topography, also known as photokeratoscopy or videokeratography, is a non-invasive medical imaging technique for mapping the surface curvature of the cornea, the outer structure of the eye. Since the cornea is normally responsible for some 70% of the eye's refractive power, its topography is of critical importance in determining the quality of vision and corneal health.

Design method of free-form surface glasses based on wave-front technology

InactiveCN102914879AImprove visual qualityMeet the characteristics of clear visionOptical partsAberrations of the eyeVisual field loss
The invention relates to a design method of free-form surface glasses based on a wave-front technology, which has the technical characteristics that length data of each part of an eye axis is substituted into an eye optical model; a cornea surface curvature and a corneal topography data replace the eye model; wave-front aberration data of actual human eyes is converted into a corresponding value under photopic vision; an individualized eye model which accords with an actual human eye visual property is established; a lens is arranged in front of the individualized eye model; the lens and the individualized eye model are considered as a uniform lens-eye optical system and a certain visual field angle is arranged for the system; a plurality of structures with different angles are arranged for the lens-eye optical system; and the free-form surface glasses according with an individual eye visual property, and the diopter and the structural parameters thereof are calculated. The free-form surface lens obtained by the design method disclosed by the invention, low-order aberration of the eyes can be corrected and high-order aberration can be better corrected; and the design method has the advantages of simplicity and convenience for designing, objectiveness and accuracy, and high precision.
Owner:天津宇光光学有限公司

Corneal topographic map discrimination method and system based on deep learning

The invention discloses a corneal topographic map discrimination method and a corneal topographic map discrimination system based on deep learning. A corneal topographic map obtained in the prior artis preprocessed to obtain corneal topographic feature data capable of being processed by a corneal topographic map discrimination model. The corneal topographic feature data is input into the cornealtopographic map discrimination model, and a corneal morphology result is obtained through the corneal topographic map discrimination model. The corneal topographic map is analyzed through the cornealtopographic map discrimination model to determine the morphological result of the corneal topographic map, a doctor can directly determine the corneal morphology according to the result output by thecorneal topographic map discrimination model, and the prediction accuracy is high. According to the corneal topographic map discrimination method and system based on deep learning provided by the invention, the trained convolutional neural network model is used for carrying out morphological discrimination on the corneal topographic map, and the problem that a corneal morphological discriminationtechnology for carrying out deep learning processing analysis on the corneal topographic map does not exist in the prior art is solved.
Owner:ZHONGSHAN OPHTHALMIC CENT SUN YAT SEN UNIV

Conic cornea recognition method and system based on multi-dimensional feature adaptive fusion

The invention discloses a keratoconus recognition method and system based on multi-dimensional feature self-adaptive fusion. The method comprises the following steps: (1) obtaining original corneal topographic map data of a plurality of independent samples by using a Pentacam anterior segment imaging system; (2) carrying out comprehensive judgment and labeling on the condition of the conic corneaon the five dimensions of each independent sample; (3) counting normal size, mean value, variance and extreme value information of original corneal topographic map data of five dimensions; (4) dividing a training set and a verification set; (5) processing topographic map data in the training set and the verification set; (6) constructing and training a residual convolutional neural network with five-dimensional feature adaptive fusion; (7) utilizing a Grad-CAM visualization mode to obtain average visualization information of the three types of test samples; and (8) performing prediction by using the trained model, and performing back propagation on the maximum prediction score to obtain a visual effect picture. According to the invention, the problem of poor recognition effect of the coniccornea in practical application can be solved.
Owner:ZHEJIANG UNIV

Visual optics analysis system

A visual optical analysis system is provided, which belongs to the technology field of medical optics. In the invention, the emergent light from a collimated laser source passes through a first light splitter and then is reflected to a cornea, the light from a flash lamp passes through an optical grating and a light-filtering projection system and then is projected onto a second light splitter, the second light splitter is positioned between the light-filtering projection system and the first light splitter, a third light splitter is provided between an aperture matching system and an imaging objective lens, an object is provided outside the third light splitter, a fourth light splitter is provided between the third light splitter and the light-filtering projection system, a part of the emergent light reflex from the cornea passes through the light-filtering projection system and then reaches a monitoring CCD, a defocusing compensation system is provided inside the aperture matching system, an astigmatism compensation system is positioned between the aperture matching system and a Shack-Hartmann wave-front sensor, and the Shack-Hartmann wave-front sensor is connected with a computer. The visual optical analysis system can accurately detect the corneal topography and the total aberration of human eyes and also accurately calculate the corneal aberration and the intraocular aberration.
Owner:SHANGHAI JIAO TONG UNIV
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