33 results about "Eye Surgeon" patented technology

The invention discloses a pair of intelligent eyesight monitoring and eye disease prediction glasses, and aims to solve the problems that most of existing eye health monitoring devices are used for regular inspection, cannot monitor and predict the eye health condition in real time and are difficult to take intervention measures in time, the glasses comprise glasses legs and a glasses main body, and the glasses main body is provided with an inner side facing a wearer; the glasses body further comprises a miniature camera, an optical sensor, a master control system and a battery system. The miniature camera is connected with the main control system through an application-specific integrated circuit, and the miniature camera is installed on the inner side of the glasses body facing the eyes of a wearer and used for shooting eye images of the wearer in real time and capturing the pupil size, eyeball movement and sight line direction of the wearer; the optical sensor is connected with the main control system and is used for detecting the ambient light intensity and color and adjusting the brightness of the lenses of the glasses main body; the eye health condition of the teenagers can be monitored and predicted in real time, and accurate health data support is provided for parents, teachers and ophthalmologists.

In some embodiments provided herein is a generative foundation model trained over millions of health system-scale electronic health records along with web-scale medical text corpora to acquire knowledge of both medical practices and theories, and use of the generative model for rare disease diagnosis (including rare ophthalmic, diseases and rare systemic diseases), emergency condition identification (including ophthalmic emergencies and systemic emergencies), complex disease solving ("diagnostic puzzles"), or generating multimodal medical imaging reports (including ophthalmic images and radiology images such as X-rays and CT scans). In some embodiments, the generative model involves the use of language data, for pre-training, language data for supervised finetuning using a instruction tuning approach (e.g., QA pairs), and a human-machine hybrid evaluation strategy. In some embodiments, both the pre-training and supervised finetuning phases involve the use of a particular method of scaling to extend the context window. In some embodiments, the human-machine hybrid evaluation strategy involves language data for automated evaluations, as well as evaluations by generalists and by different specialists (e.g., ophthalmologists and radiologists) of varying levels of experience. In some embodiments, the generative foundation model, MetaGP, is used for unmet clinical needs through integration of medical and multimodal imaging data.

The invention relates to an information distribution marketing ecosystem connecting eyewear, eyewear accessories, signs, stickers to present prescriptions, information or telemedicine connection capabilities based on NFC technology embedded or adapted onto products. The method and system comprising of using mobile applications to program eyeglasses or contact lenses prescriptions, weblink connection, product information, synergistic marketing, appointment scheduling links, and / or virtual audio telemedicine direct links into an NFC tag to one or more products such as signs, stickers, eyewear frames, eyewear accessories. NFC embedded products can be used in pharmacies, medical offices, optical retailer shops, department stores, or eye doctors' offices. The NFC tag on selected products and their parts helps to enable a user to use an NFC smartphone to touch the NFC tag, to reach information via centralized connection and / or decentralized connection using the internet.

The application provides a micro-liquid injection system and a method thereof, and relates to the technical field of medical devices, and solves the technical problem of inconvenient use of an injection device for subretinal drug injection used in the prior art. The system comprises an injection cylinder, a piston, a connecting hose, a transfusion connector, a needle, and a connecting piece. The piston is arranged in the injection cylinder. The injection cylinder is connected with the needle through the transfusion connector and the connecting hose. The injection cylinder is connected with a vitreous body cutting and ultrasonic emulsification integrated machine (hereinafter referred to as a vitreous body cutting machine) through the connecting piece. The application provides a micro-liquid injection system. By adding the transfusion connector, unidirectional conduction and instantaneous positive pressure can be generated, so that the injection of bubbles can be avoided as much as possible when an ophthalmologist or the like performs drug injection. The connecting hose is arranged between the injection cylinder and the needle, the distance between the injection cylinder and the needle is increased, and a nurse can observe the display on the syringe to remind the doctor of the drug injection amount.

A system and method for determining compatibility between multifocal contact lenses and patients seeking presbyopia vision correction includes: receiving a request from a first device associated with a first ophthalmic care professional to select a contact lens for a consumer, wherein the request includes biometric / refractional information associated with the consumer; obtaining a performance metric associated with the first ECP; determining a customized compatibility index using the machine learning model and based on the performance metric, the customized compatibility index indicating compatibility between a specific contact lens and the consumer for the first ECP; and presenting a report indicating the compatibility index on the first device. Additional systems, methods, and non-transitory machine-readable media are also provided. The idea is to replace or at least supplement the work of ophthalmologists with automated systems.

The invention provides a method and a device for detecting anterior chamber angle stenosis or closure disease accompanied by latent lens suspension ligament relaxation, and an innovative multi-modal classification model is constructed by combining OCT image features extracted by 3D-CNN and clinical parameter features based on integrated learning. After data preprocessing, key features of an SS-OCT image are automatically extracted by using a 3D-CNN model, and clinical parameters are accurately classified by training a plurality of base machine learning models and integrating results of the models by using a voting classifier. Finally, image features and clinical parameter features are fused, 3D-CNN and MLP parameters are jointly trained, feature combination is optimized, and efficient and accurate diagnosis of the relaxation state of the crystalline lens suspension ligament can be achieved on a computer. According to the method, the comprehensiveness and accuracy of computer-aided diagnosis are improved, subjective errors of manual judgment are reduced, and a powerful auxiliary tool is provided for ophthalmologists.

The present invention discloses an auxiliary analysis model for predicting corneal edema after phacoemulsification surgery for cataracts, which belongs to the field of medical technology. The model uses the best corrected visual acuity (BCVA) before phacoemulsification surgery and the cumulative released energy (CDE) during the phacoemulsification process during the surgery as indicators to construct a nomogram; wherein, the nomogram includes five line segments, each line segment is marked with a fixed scale, and the relative position of each line segment is fixed, and the five line segments are, from top to bottom, BCVA and CDE score line segments, BCVA value line segments, CDE value line segments, BCVA and CDE score total line segments, and corneal edema probability line segments; the prediction model of the present invention can complete relatively accurate predictions using only two common clinical data, has low data requirements for use, is convenient and practical, and has a high accuracy rate, can help ophthalmologists quickly and accurately judge the risk of corneal edema after phacoemulsification surgery, and assist ophthalmologists in making decisions in clinical work.

The invention discloses an intelligent glaucoma diagnosis method based on multi-task learning. According to the method, a multi-task learning network model is constructed, and the model is composed of a U-Net network and a VGG network. The U-Net network is responsible for extracting features from the eye fundus image to obtain a cup-to-disk ratio, and inputting the cup-to-disk ratio as one of the features of the eye fundus image into the VGG network, and the VGG network performs glaucoma classification on the eye fundus image by using the features. By sharing the encoder portion of the U-Net network, the two networks can share the learned feature information. After being trained by a fundus image data set, the model obtains very high glaucoma classification accuracy. According to the invention, an accurate and efficient glaucoma diagnosis function is realized, the method can be widely applied to large-scale glaucoma screening tasks, the work of ophthalmologists is greatly facilitated, and the harm of glaucoma to people is reduced.

The utility model provides a nucleus chopping action training tool in cataract ultrasonic emulsification surgery, which comprises a human eye anterior segment environment simulation device, and is characterized by further comprising a first nucleus body and a second nucleus body, the two nucleus bodies are magnetically connected through a first magnetic attraction piece to form a cylindrical simulation nucleus, and a second magnetic attraction piece is arranged between the first nucleus body and the second nucleus body. The cylindrical simulation nucleus is arranged at the position of a simulation human eye nucleus in the human eye anterior segment environment simulation device; one end face of the cylindrical simulation nucleus is an operation face, the other end face of the cylindrical simulation nucleus is a nucleus back face, and at least two grooves used for rotating the cylindrical simulation nucleus are formed in the operation face. Ophthalmologists can be taught to operate normatively during training, and can know whether training actions are accurate or not in time.

A custom lens device is disclosed as a corrective lens created by a specialized 3D printer. Specifically, a qualified technician working with an ophthalmologist and / or an optometrist combine laboratory measurements of the retina and other eye surfaces, then combine that data with subjective input from the patient's correction to an Amsler grid, to create a custom lens that will un-distort vision which has been distorted (i.e., warped), due to undulations in the retina caused by a number of eye diseases, including, but not limited to, epiretinal membrane and macular degeneration.

The embodiment of the invention relates to the technical field of cross-modal medical image generation, provides a generation method of a fluorescein angiography image and a training method of a generation model, and designs a potential diffusion model-based deep learning framework, namely the generation model of the fluorescein angiography image, the generation model is composed of two parts, one is an automatic encoder capable of encoding an image into a hidden space, the automatic encoder comprises an encoder and a decoder, the other is a diffusion network used for learning image features, and the image encoder is combined to perform staged training on the generation model by utilizing an ultra-wide-angle fundus imaging image and a corresponding fluorescein angiography image, so that the generation model is obtained. According to the method, the accuracy of model generation information is effectively improved, the generation effect of the fundus fluorescein angiography is improved, an ophthalmologist can be better assisted in completing fundus examination, and assistance is provided for diagnosis of eye diseases.

The invention relates to the field of diabetic retinopathy image segmentation, and provides a diabetic retinopathy image feature segmentation method and device, and the method comprises the steps: obtaining a to-be-segmented color fundus photo; using a pre-trained diabetic retinopathy segmentation model to segment the focus of diabetic retinopathy in the color fundus photo to obtain a corresponding segmented image; wherein the diabetic retinopathy segmentation model comprises a plurality of encoders, a plurality of multi-scale decoders and a jump connection layer, and the jump connection layer is used for directly transmitting feature maps output by the encoders to the multi-scale decoders through jump connection in an up-sampling stage of the decoders. The structure information of the fundus focus in the segmented image can be effectively improved, the focus area is clearer, prediction generation of the segmentation information is accelerated, the operation requirement is reduced, an ophthalmologist is better assisted in fundus examination, and help is provided for structure analysis of the fundus focus and diagnosis of eye diseases.

To provide an image for supporting diagnosis of a fundus by an ophthalmologist.SOLUTION: Provided is an image processing method including: a step (208) of analyzing a choroidal blood vessel image and estimating the position of a vortex vein; a step (212) of calculating a feature value indicating the positional relationship between the position of the vortex vein and the position of a specific portion of the fundus oculi; and a step of superimposing and displaying the feature value on the fundus oculi image.SELECTED DRAWING: Figure 5

To provide a schematic eye suitable as a phantom for optical coherence tomography angiography.SOLUTION: A schematic eye according to an embodiment is a phantom used to evaluate an optical coherence tomography angiography function of an ophthalmologic apparatus. The schematic eye includes a liquid storage part. In the liquid storage part, liquid with fine particles making the Brownian motion floating therein is encapsulated and stored.SELECTED DRAWING: Figure 6A

Systems and methods are provided for eye health and vision examinations. A customer diagnostic center is configured to generate customer examination data pertaining to an examination of a customer's eye. The customer diagnostic center provides a user interface for communicating with a customer and ophthalmic equipment for administering tests to the customer. A diagnostic center server is configured to receive the customer examination data from the customer diagnostic center over a network and allow the customer examination data to be accessed by an eye-care practitioner. A practitioner device associated with the eye-care practitioner is configured to receive the customer examination data from the diagnostic center server and display at least a portion of the customer examination data to the eye-care practitioner. Customer evaluation data is generated pertaining to the eye-care practitioner's evaluation of the customer examination data. An eye health report is provided to the customer via the network.

The invention discloses a corneal difference intelligent identification system and method based on deep learning, and relates to the technical field of ophthalmology medical treatment, corneal topography maps and corneal difference maps before and after a shaping lens is worn are used as input features, and the corneal difference maps are classified by identifying the position and structural integrity of a defocus ring. And a comprehensive analysis method is formed by combining review and verification of a doctor, so that the evaluation accuracy of the corneal shaping effect is improved, and the possibility of misjudgment and missed judgment is reduced. According to the method, the multi-level Resnet50 corneal difference recognition model is trained by using a large batch of data, automatic recognition and analysis of the corneal difference chart are realized, the corneal shaping effect can be quickly and accurately evaluated, the time and errors of manual analysis are reduced, and the method can replace a deep ophthalmologist to assist in judging the effect of a shaping lens.

To provide a schematic eye suitable as a phantom for optical coherence tomography angiography.SOLUTION: A schematic eye according to an embodiment is a phantom used to evaluate an optical coherence tomography angiography function of an ophthalmologic apparatus. The schematic eye includes a liquid storage part. In the liquid storage part, liquid with fine particles making the Brownian motion floating therein is stored in a non-fluid state.SELECTED DRAWING: Figure 6A

A medical image processing system and method, and a computer readable medium for processing a medical image are provided, which can be used for detecting, classifying, and / or assisting in diagnosing cataract. A data acquisition module is used to acquire an ultra-wide field fundus image, a cropping module is used to crop the ultra-wide field fundus image into a cropped image, and a deep learning module is used to detect and determine a classification of a lens opacification type corresponding to the cropped image. Therefore, an automatic screening for cataract can be realized with an increased detection rate and a decreased false negative rate, and ophthalmologists can thus cut down diagnosis time with increased examination efficiency. Also, telemedicine can be achieved accordingly.

Consumer products such as refractive measurement devices can be used to obtain refractive measurement results, allowing consumers to track their vision without visiting an optometrist or ophthalmologist. Such consumer products can work in conjunction with a smartphone or other product with a touch screen that presents an image to the refractive measurement device. Smartphones may have a resolution ratio, sometimes measured in PPI or pixels per inch that is unknown to the user and / or the refractive measurement device. One aspect of the present invention is to provide an optical interface for a user to manually match the viewing port boundaries of a smartphone to coincide with the viewing port boundaries of a refractive measurement device. Another aspect of the present invention is the use of pre-distortion in the image presented to the user. By noting the corrective actions applied by the user on the refractive measurement device, the user's own refractive error can be derived.

The invention belongs to the technical field of medical image processing and intelligent medical diagnosis, and particularly relates to an ophthalmic disease identification method based on an ophthalmic visual basic model. The ophthalmic disease identification method comprises the following steps: inputting a to-be-detected fundus image into an ophthalmic visual basic model to obtain a disease prediction result of the to-be-detected fundus image; wherein the ophthalmology vision basic model is obtained by training by adopting the training method in the first aspect; the disease prediction result comprises a disease type, a lesion position and a lesion severity degree. According to the ophthalmic disease recognition method, an efficient and comprehensive auxiliary diagnosis tool is provided for ophthalmologists, and the accuracy and efficiency of ophthalmic disease diagnosis are improved.

The utility model discloses a pair of adjustable novel envelope scissors, which comprises a handle body and movable grooves, the movable grooves are respectively arranged on two sides of the top of the handle body, a group of scissors blades are movably assembled in each movable groove, a fixed buckle is fixed in each movable groove, a knob is arranged on the top of each scissors blade, the knob is embedded in the fixed buckle, and the handle body is fixed on the handle body. A pull rod is fixedly connected to the root of the shear blade, a plurality of sets of protruding blocks are distributed on the inner wall of the fixing buckle, and a plurality of sets of teeth are distributed on the outer wall of the rotary knob. According to the pair of adjustable novel capsular scissors, the scissor blades, the pull rod, the fixing buckle and the knob are arranged, the angle-adjustable scissor blades are arranged at the front end of the scissors, and when the pair of adjustable novel capsular scissors is used, the pull rod is pulled, so that the fixing buckle and the knob overcome friction force to rotate relatively and are clamped and locked, and the shearing angle of the scissor blades can be adjusted; by means of the structure, an ophthalmologist can more easily treat the portion, difficult to reach, below the incision, and the membrane opening is prevented from being torn, so that the risk of postoperative complications is reduced, and the problem that the portion below the membrane incision is not easy to treat is solved.

A method for identifying patients comprises the following steps: determining (S10) first identification data during a first measurement of a patient (P) by means of a first measuring device (1) for determining measurement data obtained by an ophthalmologist and / or optometrist; and determining (S30) a patient ID of the patient on the basis of the determined first identification data. The invention also relates to a system and to a computer program (product).

A portable diopter examination and diagnosis instrument based on DeepSeek is an AI device integrating DeepSeek, a diopter examination and diagnosis instrument lens, a tablet personal computer and an electric holder, and can conveniently provide an accurate digital diopter detection scheme and excellent user vision correction examination and diagnosis experience for a patient. DeepSeek is used as an assistant of a virtual ophthalmologist, high-adjustment intervention of DeepSeek enables the traditional diopter adjustment ophthalmology industry to have a high technology, an intelligent treatment edge tool is added for the ophthalmology industry, and the diopter and risk of ametropia of a patient can be detected according to internationally universal refraction criteria. Therefore, in the industry of optical glasses with medium normal moment, an angle of artificial intelligence technology innovation is opened. Therefore, the portable diopter examination and diagnosis instrument based on DeepSeek has important practical significance, at least brings a revolution with the times to the field of ophthalmology, and is quite wide in application prospect.

The present invention discloses a corneal difference intelligent recognition system and method based on deep learning, which relates to the field of ophthalmic medical technology. It uses corneal topography before and after wearing orthokeratology lenses and corneal topography corneal difference maps as input features, classifies corneal difference maps by identifying the position and structural integrity of the defocus ring, and combines the doctor's review and verification to form a comprehensive analysis method, which improves the accuracy of the evaluation of corneal reshaping effects and reduces the possibility of misjudgment and missed judgment. The present invention uses a large amount of data to train a multi-level Resnet50 corneal difference recognition model to achieve automatic recognition and analysis of corneal difference maps, which can quickly and accurately evaluate the corneal reshaping effect, reduce the time and error of manual analysis, and can replace senior ophthalmologists to assist in judging the effect of orthokeratology lenses.

This is a system and method for determining a patient's prescription for corrective lenses using predictive calculations and corrected-eyesight simulation. Together, these technologies act as a digital substitute for phoropter testing, thus reducing the cost, time, and human error associated with an eye exam. Based on age, gender, autorefractor readings, and environmental factors, a patient specific model is calculated and fed into a visual simulation tool. From this simulation, an eye care professional is able to determine the patient's corrective lens prescription.

The invention consists of forceps with rounded gripping tips. These rounded tips are designed to prevent perforation of the amniotic membrane during its insertion onto the ocular surface for the treatment of dry eye and ocular inflammation, as well as to prevent injury to the conjunctiva during its removal. The forceps have gripping tips at their distal end, one of which has a notch on its inner surface. The dimensions of the notch allow the ophthalmologist to securely grasp the edge of the amniotic membrane to facilitate its insertion and removal from the ocular surface.

The integrated cataract examination and diagnosis instrument based on the artificial intelligence technology is a device combining the artificial intelligence technology, a slit lamp magnifying lens, an Android smart phone, a rotating holder and an electric push rod, and the artificial intelligence technology serves as an excellent assistant of a virtual ophthalmologist; in addition to the deep learning reasoning ability, the system can quickly and accurately provide an accurate cataract number examination and diagnosis scheme and excellent examination and diagnosis experience of user vision correction for patients according to international cataract CNP turbidity grading criteria, so that intelligent elements are added for the ophthalmology industry, and the ophthalmology industry is more intellectualized. The innovation corner of the artificial intelligence technology in the ophthalmology field is opened; therefore, the appearance of the integrated cataract examination and diagnosis instrument based on the artificial intelligence technology has important practical significance, at least a real revolution with times is brought to the current Lancanic ophthalmology field, and the application prospect of the integrated cataract examination and diagnosis instrument is very wide.

The present invention relates to an instrument and method comprising a system for projecting structured light in the form of points onto a specific area, such as the cornea of ​​the eye. It also includes an observation system for capturing and recording images on a computer, as well as a method that uses computational algorithms to triangulate the information and derive corneal topography and pachymetry, including conjunctival-scleral topography, from a single image without the need for scanning. The results of the method for determining the topography and pachymetry are displayed on a monitor. Furthermore, it uses fewer optical elements and does not require a stereoscopic system for triangulation, making it more cost-effective compared to commercial clinical instruments that require scanning to cover the entire cornea by projecting a flat beam of light obtained from a slit lamp.Furthermore, obtaining corneal information is simplified with a single image, and the results are useful for optometrists and ophthalmologists, as well as the ophthalmic industry, because in addition to the eye, it can also be applied to a variety of lenses.

The present application relates to the field of electronic information technology, and in particular to a color fundus image quality evaluation method based on ensemble learning, which comprises data set division, and the data set comprises a color fundus IQA data set and a segmentation data set, 80% of the data of the data set is randomly selected as a training set, and the remaining 20% of the data is a validation set. ResNet-18 model and U-Net model are trained separately without interference. 50% (proportion adjusted according to data volume) of the images in the color fundus IQA data set training set are manually labeled with 5 features, and the 5 features are contrast, focus, illumination, shadow and reflection. The CF image quality evaluation method based on ensemble learning provided in the present application meets the actual needs of an ophthalmic clinic and can comprehensively evaluate the CF image taken on site to determine whether the image is suitable for ophthalmologist diagnosis.

The invention relates to a modular Modular Laser Therapy Device (MLTD) to be used by ophthalmologists for eye surgery that integrates three most frequently used therapeutic devices into a single, compact unit enabling the treatment with capsulotomy, vitreolysis and iridotomy, with selective laser trabeculoplasty and with photocoagulation. While providing such modular laser device a method is provided for optomechanically coupling different ophthalmic modules into the single unit using two laser sources.