18 results about "Eye anterior segment" patented technology

A glaucoma treatment apparatus including an imaging device capable of imaging the anterior segment of the eye, a treatment laser, an algorithm programmed to determine a location and a cross sectional area of a treatment based on a customized anatomy of the anterior segment of the eye including the trabecular meshwork (TM), the Schlemm's Canal (SC) and collector channels (CCS), obtained from pre-operative images of the anterior segment of the eye, a pre-operative intraocular pressure (IOP) level and a target IOP reduction as an inputs, and a processor configured to actuate the apparatus to create an outflow channel with a cross-sectional area and location or multiple outflow channels with multiple cross-sectional areas and locations from the anterior chamber (AC) to the SC across the TM, as determined by the algorithm to achieve the target intraocular pressure (IOP) reduction. Also disclosed is a method of reducing intraocular pressure in an eye.

[Problem] To provide a technology with which it becomes more likely to be able to select a posterior chamber phakic intraocular lens having a size suitable for a subject's eye. [Solution] Provided is a simulation system comprising: an acquisition unit that acquires a non-insertion image, which is an image, captured by a tomographic device, of an anterior ocular segment of a subject's eye into which a posterior chamber phakic intraocular lens has not been inserted; a generation unit that generates, on the basis of the non-insertion image and the size of a posterior chamber phakic intraocular lens to be inserted into the subject's eye, an insertion image, which is an image of the anterior ocular segment of the subject's eye into which the posterior chamber phakic intraocular lens has been inserted; an identification unit that identifies, on the basis of the insertion image, an optimal size, which is the optimal size of the posterior chamber phakic intraocular lens to be inserted into the subject's eye; and an output unit that outputs information relating to the optimal size.

The invention discloses an ophthalmology ultrasound RF signal enhancement method and device and a model training method and device, and relates to the technical field of ophthalmology ultrasound and the technical field of deep learning, and the method comprises the steps: obtaining to-be-enhanced ophthalmology ultrasound RF signal data of a target object, the to-be-enhanced RF signal data is obtained by performing ophthalmologic ultrasonic scanning on eyeballs of a target object through eyelids by adopting high-frequency pulse sound waves; rF signal data to be enhanced are input into a pre-trained signal enhancement model, blind deconvolution calculation is carried out on the RF signal data to be enhanced, obtained output serves as enhanced RF signal data, and the signal enhancement model is a deep learning model. By the adoption of the scheme, the comfort level of a patient during anterior segment ophthalmic ultrasonic examination is improved, and the examination efficiency is improved.

The invention discloses an ophthalmological diagnostic instrument, and relates to the technical field of medical equipment.The ophthalmological diagnostic instrument comprises a topographic map structure, a crack projection structure, an off-axis imaging structure, a dichroic optical element and a rotating mechanism, opaque circular rings and semitransparent circular rings which are alternately distributed are arranged on the Praxiso disc, the red light source is configured to perform backlight illumination on the semitransparent circular rings, and the first camera is a color sensitive image sensor, is aligned along the visual axis of the eye and is used for capturing a Praxiso pattern reflected by the surface of the cornea and a color image of the anterior segment of the eye; the fissure projection structure comprises a visual axis along the topographic map structure and projects a blue fissure light beam to the anterior segment, the off-axis imaging structure comprises a second camera, the second camera is obliquely arranged relative to the visual axis and is used for capturing an anterior segment cross section image irradiated by the blue fissure light beam, and the dichroic optical element is arranged along the visual axis.

To provide an ophthalmic device that can measure corneal shape without increasing the subject's discomfort due to glare. [Solution] An ophthalmic device for measuring the corneal shape of an eye under examination, comprising: a first projection optical system that projects a first pattern indicator onto the cornea of ​​the eye under examination using invisible light; a second projection optical system that projects a second pattern indicator onto the cornea of ​​the eye under examination using visible light; an anterior segment imaging optical system that receives reflected light from the anterior segment of the eye under examination; and a control unit, wherein the control unit analyzes and processes imaging data obtained by receiving the reflected light of the first pattern indicator projected onto the cornea of ​​the eye under examination by the first projection optical system with the anterior segment imaging optical system to determine whether or not corneal shape measurement of the eye under examination can be performed, and if it is determined that corneal shape measurement is possible, the second projection optical system projects a second pattern indicator onto the cornea of ​​the eye under examination, and analyzes and processes imaging data obtained by receiving the reflected light of the second pattern indicator with the anterior segment imaging optical system to measure the corneal shape.

This invention discloses a method and device for anterior segment Sham elastography. This invention combines micron-level spatial resolution, high cost-effectiveness, and clinical operability. It can obtain quantitative elastic distribution of anterior segment tissues such as the cornea in vivo and in situ, providing reliable biomechanical basis for ophthalmic diagnosis and treatment scenarios such as early screening of keratoconus, refractive surgery planning, and glaucoma risk assessment. Compared with the prior art, the system structure of this invention is simplified, the cost is significantly reduced, and it has higher resolution and achieves truly non-contact measurement.

The invention discloses a slit lamp microscopic imaging device integrated with a fundus observation function, and belongs to the technical field of ophthalmology detection, and the device comprises a moving base, a jaw bracket, a light source supporting arm, a microscope supporting arm, a slit illumination assembly, a fundus illumination assembly and a microscopic observation assembly; a central shading diaphragm is arranged on a newly added fundus lighting light path, a front collecting lens capable of movably moving in or out of the light path is arranged between the plane mirror and the microscopic observation assembly, and light combination of the crack lighting light path and the fundus lighting light path is achieved through a beam splitter prism. According to the invention, the central energy of the light beam irradiated to the cornea can be reduced, the fundus examination safety is improved, the interference of cornea reflection stray light is effectively avoided, the fundus imaging quality is improved, the integrated detection of the anterior segment and the fundus tissue is realized, and the efficiency and stability of ophthalmic clinical detection are improved.

A method for constructing a personalized human eye model. This includes the following steps: (1) simplifying the structural parameters of the human eye to establish a personalized three-dimensional full-eye geometric model; (2) determining the viscoelastic material parameters of the human cornea; (3) using fluid-structure interaction to simulate the actual boundary conditions of the human eye, analyzing the changes in the actual state of the human eye, selecting appropriate element types, discretizing the model into a finite number of aggregates, completing the construction of the finite element human eye model, and solving the model using finite elements; (4) simulating optical coherence elastography of the anterior segment tissues such as the cornea. Considering the individual differences in the geometric morphology and tissue material parameters of the human eye, based on clinical ophthalmological diagnostic data, a personalized full-eye model containing complete geometric morphological information of the human eye was established in finite element software using an elastography method, providing theoretical guidance and technical support for ocular tissue optical coherence elastography equipment.

The application discloses a kind of early warning method and device of children's eye disease and systemic genetic syndrome, it is related to ophthalmic examination equipment technical field.The method includes: collection ocular anterior segment image data set, utilize the multi-task segmentation model after training, obtain multiple congenital eye disease quantitative feature data, then based on the risk index calculator of pre-established index calculation is carried out, and the congenital eye disease risk index is obtained, classification processing is carried out, matches eye abnormal phenotype, and obtains systemic disease early warning report.The application can realize more than 10 kinds of congenital eye disease and rare but important lesion in one examination screening, and simultaneously establishes the intelligent early warning system of eye phenotype and systemic genetic syndrome.

This invention relates to the field of medical image analysis technology, specifically disclosing a method and system for anterior segment image analysis. The method includes: acquiring anterior segment images and extracting features to obtain shared features; inputting the shared features into coarse-grained and fine-grained branches respectively to obtain output features of the coarse-grained and fine-grained branches; performing asymmetric feature fusion with gradient stopping, and then passing the results through corresponding classifiers to obtain anatomical classification prediction results of the coarse-grained branch and disease classification prediction results of the fine-grained branch. This invention jointly models coarse-grained anatomical features and fine-grained disease representations, which can significantly improve recognition accuracy and model generalization ability, realize automated analysis of ophthalmic images, and promote the widespread application of intelligent medical technology in clinical practice.

The invention provides an anterior segment index measurement method and system, computer equipment and a storage medium, and belongs to the field of medical image processing and computer vision. Comprising the following steps: acquiring an eyeball OCT image of a target object; extracting multi-scale texture features of the eyeball OCT image, and converting the texture features into structural features; converting the structural features into spatial domain enhancement features and frequency domain enhancement features in the spatial dimension and the frequency dimension respectively; fusing the spatial domain enhancement feature and the frequency domain enhancement feature to obtain a fused full-dimensional feature; generating eye tissue contour features according to the full-dimensional features; and measuring and calculating based on the eye tissue contour features to obtain the anterior segment biological index. According to the method, the segmentation precision of the tissue boundary in the complex eyeball OCT image can be effectively improved, and automatic and high-precision calculation of multi-dimensional indexes is realized.

The application relates to the field of image processing and discloses an OCT conjugate mirror image removing method and device based on deep learning, which comprises the following steps: constructing a complex conjugate image of spectral data, constructing a true anterior eye segment image of the spectral data, performing image preprocessing on the complex conjugate image and the true anterior eye segment image; analyzing a pseudo-anterior eye segment image corresponding to the preprocessed conjugate image, calculating an absolute value loss between the pseudo-anterior eye segment image and the preprocessed anterior eye segment image; discriminating the falsity between the pseudo-anterior eye segment image and the preprocessed conjugate image, discriminating the authenticity between the preprocessed conjugate image and the preprocessed anterior eye segment image, calculating a generative network loss of a generative network; performing model training on a pre-trained neural network model to obtain a trained neural network model; performing model verification on the trained neural network model to obtain a verified neural network model, calculating a peak signal-to-noise ratio of the verified neural network model, and selecting a final neural network model. The application can reduce the difficulty of removing the OCT conjugate mirror image.

The invention discloses a method for predicting the arch height after implantation of an intraocular lens with a lens eye, and relates to the technical field of intraocular lens implantation, and the key points of the technical scheme are as follows: obtaining a trained postoperative image prediction model, a superposition loop algorithm, and inputting preoperative images, clinical parameters and refractive parameters of the intraocular lens with the lens eye; the method comprises the following steps: firstly, carrying out PIOL diameter detection on the eye anterior segment, carrying out enumeration input on the PIOL diameter, and outputting a postoperative OCT (Optical Coherence Tomography) prediction image of the eye anterior segment; identifying features of the postoperative anterior segment OCT prediction image, and calculating an arch height value by using the image features; and judging whether the arch height value is in a safety range, and if the arch height value is in the safety range, outputting a recommended PIOL diameter and a corresponding prediction image, and predicting the arch height value. According to the method, the postoperative arch height prediction precision of the PIOL operation is improved, and the experience dependence of artificial lens diameter selection is reduced, so that the postoperative arch height standard reaching rate is improved, the secondary operation probability is reduced, and the complication risk is reduced.

This application relates to the field of intelligent intraocular lens (IOL) selection, specifically disclosing an intelligent IOL selection system for cataract surgery based on ocular bioparameters. The system is not limited to the acquisition of traditional static geometric data such as axial length and corneal curvature, but further utilizes a deep convolutional neural network to extract texture features and perform dimensionality reduction mapping on anterior segment tomographic images, thereby resolving the capsular bag compliance feature vector characterizing the biomechanical properties of the ocular soft tissue. Based on this, the geometric parameters of the patient's eye, capsular bag compliance features, and the mechanical and physical properties of the IOL are combined. By introducing a physical constraint mechanism, the mechanical equilibrium state after lens implantation is simulated, thus accurately predicting the effective lens position. This effectively addresses the fitting challenges of non-standard eyeballs or special lens models, significantly improving the accuracy and stability of postoperative refractive prediction.

The utility model provides an ophthalmology measuring system with a double-optical-wedge prism group, which realizes efficient and accurate ophthalmology OCT (optical coherence tomography) imaging. The system comprises an OCT imaging module which comprises an OCT light source, a reference arm module, an OCT sample arm module, an optical fiber coupler and a detector. The sample arm module is integrated with an optical path switching scanning device and can guide detection light to a posterior segment or anterior segment optical path. A double-optical-wedge prism group is introduced and comprises a fixed prism and a movable prism, and the movable prism can translate relative to the fixed prism to dynamically adjust the optical path. The design is combined with the Doppler frequency shift technology, the detection depth of the system is remarkably enhanced, meanwhile, the imaging resolution is kept, and high-cost equipment does not need to be additionally added. The system can rapidly switch imaging modes, realizes accurate imaging of different parts of the eyes, improves the measurement speed and accuracy, reduces the cost, and is suitable for clinical ophthalmic diagnosis.

A method for determining the relationship between preoperative measurements of the anterior segment of a patient's eye and the postoperative position and optional tilt of the implanted intraocular lens (IOL) is described, based on quantitative optical coherence tomography (OCT) of the patient's eye and a machine learning architecture for determining the optimal regression model. Formulas obtained using this method are further described to determine estimated lens position (ELP) and optional tilt from preoperative measurements in the patient, to be incorporated into IOL refractive power calculation formulas or ray-tracing-based IOL refractive power selection.

The application belongs to the technical field of three-dimensional reconstruction of the anterior segment system, and discloses a slit lamp anterior segment three-dimensional reconstruction method, system, device and terminal, which comprises the following steps: S1, calculating a plurality of local homography matrices for camera calibration; S2, scanning a series of images of the anterior segment system; S3, performing edge extraction to obtain a pixel point set on the slit lamp projection stripe on the scanned image; S4, performing image region segmentation to further distinguish the cornea, iris, lens and other parts; S5, using the camera calibration parameters to transform the pixel point set on each scanned image to the world coordinates; S6, adjusting the three-dimensional point set corresponding to the cornea, iris, lens and other parts according to the refraction law, and simultaneously performing point cloud gridding to obtain a three-dimensional model of the anterior segment system; the application proposes a method for using a slit lamp to perform three-dimensional reconstruction of the anterior segment system, and overcomes the problems of other methods, such as high cost and inaccurate reconstruction results.