289 results about "Macula Lutea" patented technology

The subject invention pertains to deep learning (DL) systems and methods for the binary classification of Alzheimer's Disease. Optical coherence tomography (OCT) generated reports were used, and the images were grouped into 3 different inputs: (1) an optic nerve head (ONH) model including a retinal nerve fiber layer (RNFL) thickness map, a RNFL deviation map, and an ONH-centered en face image; (2) a Macula model including a ganglion cell inner plexiform layer (GCIPL) thickness map, a GCIPL deviation map, a macular thickness map, and a macula-centered en face image; and (3) a General model including all images of (1) and (2). A fusion network is provided to analyze the plurality of images from a single eye for classification. The fusion network includes Feature Extraction, Feature Fusion, and Feature Reconstruction. Ensemble learning is provided to advantageously combine several baseline models to build a single but more powerful model.

The microstructure lens comprises a substrate, the substrate is provided with a bright vision area, a first optical area and a second optical area, and the first optical area and the second optical area are arranged around the bright vision area; the first optical area is located between the bright visual area and the second optical area and connected with the bright visual area and the second optical area. The bright vision area is used for generating a clear vision signal; the first microstructure array is arranged in the first optical area and is used for being matched with the substrate to provide a visual signal for stimulating the periphery of the retina; and the second microstructure array is arranged in the second optical area and is used for being matched with the substrate to provide at least two different visual signals for stimulating the periphery of the retina. The first optical area provides single-effect stimulation to compensate relative peripheral diopter close to the center of the retina macular, and lens wearing adaptability of a patient is considered; the second optical zone provides multiple-effect stimulation to compensate for gradually increasing relative peripheral diopter around the retina and delay the time of drug resistance generation of the product, thereby enhancing myopia management efficacy and prolonging efficacy time.

According to the maculopathy diagnosis device and method based on GCN and Mama cooperation and the medium, feature interaction processing is carried out by designing a GMMN module (a graph mapping Mama network), each pixel is regarded as a feature node, and through combination of graph convolution and Mama coding, the advantages of the two methods are brought into full play, and the respective limitations of the two methods are overcome at the same time. Furthermore, a mapping module is developed, and effective cross-branch feature fusion is realized by using a geometrical relationship between feature nodes. A large number of experimental results prove that the network has excellent performance when the CFP modal image is used for automatic diagnosis of macular edema, and the effectiveness and clinical application potential of the method are verified. According to experimental verification on two public data sets of IDRID and Messidor and one private data set, 91.26%, 94.58% and 98.43% of diagnosis accuracy are achieved respectively, it is indicated that the method can achieve a good diagnosis effect on different data sets, and the huge potential of the method in clinical application is highlighted.

The invention provides a two-stage current intensity adjusting method for an eye therapeutic apparatus, and the method comprises the steps: extracting the impedance effect intensity of a current at a macular center through recognizing the thickness of an impedance barrier layer corresponding to the current limiting degree of a high-impedance region, and combining with the actual penetration thickness, and obtaining the current penetration depth reduction proportion of the current penetration depth at the macular center; the current intensity imbalance degree of the coarse adjustment basic current intensity in the transition subarea is evaluated, and by obtaining the current intensity increase and decrease multiple of the fine adjustment compensation current intensity, the gradient difference between high impedance limitation and low impedance permeation is integrated, and the current intensity is compensated to balance the current intensity imbalance degree of the transition subarea; and updating the current output power level of each partition according to the fine adjustment compensation current intensity, and feeding back the current output power level to a therapeutic instrument circuit in real time to obtain uniform therapeutic intensity distribution so as to be matched with the decreasing proportion of impedance of impedance gradient distribution from high to low.

Diabetes is a disease characterized by high levels of blood glucose. It is important to keep diabetes under control to avoid short- and long-term complications. Diabetes can affect vision due to the alterations it produces in the blood vessels of the retina. This is known as Diabetic Retinopathy (DR), which is one of the leading causes of impaired vision in developed countries. One of the complications of diabetic retinopathy is Diabetic Macular Edema (DME), which is the leading cause of vision loss in diabetic patients and can appear at any stage of diabetic retinopathy. This consists of the gradual accumulation of fluid in the macula, the most important area of the retina. The determination of diabetic macular oedema is very important for the retina. The determination of diabetic macular oedema is very important for adequate treatment of this condition. A variety of technological options are used for detecting diabetic retinopathy, although only the most sophisticated detect macular oedema, a complication that appears as a consequence of diabetic retinopathy and is one of the leading causes of blindness. The invention describes a portable system for detecting diabetic macular oedema by capturing a fundus image using a portable ophthalmoscope; said image is sent via wired or wireless means to an embedded system that has an algorithm based on artificial intelligence, which extracts information from the image and processes same to identify the presence of the condition being studied.

The invention belongs to the technical field of nano-drugs, and discloses a multifunctional nano-drug delivery system for treating neovascular eye diseases and a preparation method of the multifunctional nano-drug delivery system. The nano drug delivery system disclosed by the invention is a composite nano preparation which takes dendritic mesoporous silica nanoparticles as a carrier and co-loads cerium zirconium oxide nano enzyme and an anti-VEGF (vascular endothelial growth factor) drug, various active oxygen can be efficiently removed, oxygen is continuously released through catalytic decomposition of hydrogen peroxide, a retina hypoxia microenvironment is improved, and the retina hypoxia effect is improved. According to the present invention, the anti-VEGF drug delivery system can reduce the oxidative stress induced retinal pigment epithelial cell apoptosis rate, reduce the inflammatory reaction, and simultaneously achieve the slow release and the controlled release of the anti-VEGF drug, and the drug effect maintenance time can achieve more than 60 days, such that the multi-target synergistic treatment can be achieved through the synergistic regulation of the multiple pathological links such as oxygen deficit-oxidative stress-inflammation-angiogenesis, and the anti-VEGF drug delivery effect can be achieved. The choroidal neovascularization can be effectively inhibited by single intravitreal injection, and a new strategy of multi-target collaborative treatment is provided for neovascular macular degeneration and other eye diseases.

The invention relates to a diabetic retinopathy fundus photography grading report system combined with a clinical guide, based on an artificial intelligence deep learning technology, and belongs to the field of fundus lesion analysis. The system accurately identifies and segments various lesions such as microhemangioma, bleeding, exudation and the like and symbolic structures such as optic discs, macular regions and the like by automatically analyzing fundus photographic images. The system adopts ICDR international standards to grade diabetic retinopathy, and provides diagnosis and treatment suggestions for lesion characteristics in combination with clinical guidelines of American ophthalmology institute in 2019. Through big data training, the system can generate detailed reports in real time, the early screening rate is remarkably improved, misdiagnosis and missed diagnosis are reduced, and the diagnosis speed and accuracy are improved. The system comprises a plurality of modules, such as an image pre-classification module, a deep learning focus recognition module, an ICDR grading module and a report generation module, efficient and accurate diabetic retinopathy diagnosis and grading are cooperatively achieved, and the clinical management level is improved.

Systems and methods relate to processing optical tomography coherence (OCT) images to predict characteristics of a treatment to be administered to effectively treat age-related macular degeneration. The processing can include pre-processing the image by flattening and / or cropping the image and processing the pre-processed image using a neural network. The neural network can include a deep convolutional neural network. An output of the neural network can indicate a predicted frequency and / or interval at which a treatment (e.g., anti-vascular endothelial growth factor therapy) is to be administered so as to prevent leakage of vasculature in the eye.

A method and apparatus for generating a visual field pattern which serves as a subjective test protocol to evaluate central vision using dynamic image generation to prevent the brain from filling-in to provide better results of patient feedback and reporting of locations of visual disturbance. This enables effective central vision testing to detect the presence of visual field disruptions including scotoma, visual-neurological perceptual effects such as filling-in, and Troxler fading. The present method and apparatus can be used for vision monitoring and self-assessment, and more particularly for monitoring vision for damage or disease to the macula or retina.

A classification method and a classification device for classifying a level of an age-related macular degeneration are provided. The classification method includes the following. An object detection model and a first classification model are pre-stored. A fundus image is obtained. A bounding box is generated in the fundus image according to a macula in the fundus image detected by the object detection model. An intersection over union between a predetermined area and the bounding box in the fundus image is calculated. A classification of the fundus image is generated according to the first classification model in response to the intersection over union being greater than a threshold.

Embodiments disclosed herein can provide ocular photo-bio- stimulation through light stimulation of specific wavelengths to the eye's retina, and to the entire eye's retina, the retina peripheral to the fovea, and / or the retina peripheral to the macula. In certain embodiments, the light stimulation is targeted at or to the rods. In other embodiments, the light stimulation is targeted at or to the ganglion cells or it is targeted at or to the rods and the ganglion cells, wherein the ganglion cells targeted or stimulated are the melanopsin containing ganglion cells (ipRGCs) or can also be called mRGCs.

According to the spectacle lens design method and the spectacle lens provided by the invention, the surface type basic parameters of the spectacle lens are determined by acquiring the spectacle fitting basic parameters and the eyeball morphological characteristic parameters of a spectacle fitting person, and then the contrast ratio of rod cells is reduced by designing a radial inhibition function, so that the visual burden of the peripheral area of macular is relieved; the surface of the spectacle lens is precisely processed through a laser direct writing technology, a complex microstructure is realized, the precise implementation of a designed radial inhibition function is ensured, and the spectacle lens is further coated through a multi-layer coating technology, so that the transmission ratio of short-wavelength light is increased; the S-cone cells are activated, and the cone cell contrast ratio is reduced, so that the eye axis growth is better regulated and controlled, and the myopia progress is slowed down.

A system and method are provided for bimodal detection and / or imaging of macular pigments. Fundus autofluorescence spectroscopy is applied in a first and a second region of an eye to measure fluorescence values from the fluorescing pigment (e.g., lipofuscin). The first region can be a macula, which has a higher density of macular pigments, and the second region can be in the peripheral retina, which has a lower density of macular pigments. Fundus reflection spectroscopy is applied in the first and a second region of an eye, as a baseline image, to determine absorptions due to other pigments (e.g., melanin) than the macular pigments and the fluorescing pigment. The density of macular pigments is determined using the measures fluorescence values and the absorptions due to other pigments.

The invention relates to a diabetic macular edema treatment effect prediction system, method and equipment, and belongs to the technical field of biomedicine. Comprising the steps of obtaining and preprocessing clinical data of a patient before treatment to obtain effective data; performing feature screening on the data to obtain feature data; constructing a prediction model, and training the prediction model by using the feature data to obtain an optimal vision recovery prediction model and an optimal edema regression prediction model; according to the two types of prediction models, a combined prediction model is constructed by adopting logic weighted fusion; inputting clinical data of a patient to be treated into the two types of prediction models to obtain a prediction result; and according to a prediction result, carrying out interpretability analysis on the optimal prediction model and the combined prediction model to obtain key characteristic variables, and further obtaining the probability of vision recovery and edema regression of the to-be-treated patient after treatment. According to the method, comprehensive and multi-dimensional sources of prediction variables are ensured, and the limitation of only depending on image data or subjective evaluation is effectively overcome, so that the prediction precision is improved.

A method and system for generating a treatment output for a subject with DME includes receiving OCT imaging data for a retina of a subject at a first and a second point in time. Using the OCT imaging data for the first and second point in time, a first and a second OCT segmented image may be generated using a machine learning model. Based on the first and second segmented OCT images, a first and a second measurement of a DME-associated feature may be generated for the first and second point in time. A reduction between the first and second measurements may be identified and compared to a threshold. A reduction that exceeds the threshold may be associated with an improved vision health metric for the subject at a third point in time. Based on the comparison, a treatment output may be generated.

Implantable medical devices for use in or on the eye. An implantable device may have at least one electrode thereon for issuing therapy, such as via electrical current or voltage, while implanted in or on the eye, for the treatment of one or more of macular degeneration, glaucoma, presbyopia, or other condition or disease of the eye. The implantable device may comprise a transducer for receiving power from an external device that may be worn on the patient using any of optical, inductive, mechanical or radiated energy. An example includes an implantable device for placement on the retina which has a gap or opening to place electrodes near the maculae without covering the fovea. Other examples may target other portions of the eye anatomy.

Described is an ophthalmic device that contains visible light filters. The ophthalmic device is a free radical reaction product of a reactive mixture comprising: one or more monomers suitable for making the ophthalmic device; a first visible light filtering compound, the first visible light filtering compound having a visible light absorption maximum between 430 and 480 nm and a full width half maximum (FWHM) at the visible light absorption maximum of at least 35 nm and up to 150 nanometers, wherein the compound is photostable, and wherein the compound has a molar extinction coefficient of at least 7740 L·mol−1·cm−1; and a second visible light filtering compound. The devices may provide one or more benefits to wearers, including enhanced macular pigment optical density (MPOD), as well as improved color perception and color enhancement.

The embodiment of the invention provides a method for acquiring maculopathy edema features in a retina image and electronic equipment, and relates to the technical field of image recognition. The method for acquiring the maculopathy edema features in the retina images comprises the following steps: acquiring a current retina image to be recognized in a plurality of retina images; determining an edema brightness threshold value of the current retina image based on the brightness value of the pixel in the vitreous body region of the current retina image; based on the brightness value of each pixel in the current retina image and an edema brightness threshold value of the current retina image, an edema area in the current retina image is determined, and the brightness value of the pixel in the edema area is smaller than the edema brightness threshold value. According to the invention, feature extraction can be carried out on the macular oedema region in the image based on the brightness value of the pixel in the retina image.

Described is an ophthalmic device that contains visible light filters. The invention provides an ophthalmic device that is a free radical reaction product of a reactive mixture comprising: one or more monomers suitable for making the ophthalmic device; a first visible light filtering compound, the first visible light filtering compound having a visible light absorption maximum between 430 and 480 nm and a full width half maximum at the visible light absorption maximum of at least 35 nm and up to 150 nanometers, wherein the first visible light filtering compound is photostable, and wherein the first visible light filtering compound has a molar extinction coefficient of at least 7740 L·mol−1·cm−1; and a second visible light filtering compound having a visible light absorption maximum between 480 and 530 nm and a full width half maximum of at least 50 nanometers and up to 150 nanometers. The reactive monomer mixture may also contain a third visible light filtering compound. The devices may provide one or more vision benefits, including enhanced macular pigment optical density as well as improved color perception and color enhancement and diminished visual artifacts.

The embodiment of the invention provides a para-center fixation detection method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring an eye fundus image of a to-be-detected person; determining macular center position information corresponding to the eye fundus image according to the eye fundus image of the to-be-detected person; according to the macula lutea center position information and the preset macula lutea fixation area, the para-center fixation type corresponding to the fundus image is determined, through the quantification technology and the visual calculation technology, analysis of the fundus image is rapidly completed, the examination time is shortened, the diagnosis efficiency is improved, whether a patient has para-center fixation or not can be more accurately judged, and the patient experience is improved. And errors caused by subjective judgment are reduced.

Illustrative methods and devices for providing stimulus to the eye to treat vision disorders. Systems and methods for testing thresholds and configuring the stimulation for a patient are provided. Various examples may include therapies for vision disorders that can progress to blindness, such as macular degeneration or other diseases and disease processes.

This invention discloses an ophthalmic disease diagnostic system based on optical coherence tomography (OCT), comprising: an image data acquisition module for acquiring OCT image data; a feature extraction and similarity calculation module for extracting OCT image feature representations and layered structural features of the macular region, calculating macular structural similarity information between different OCT image data, and constructing a structural similarity alignment matrix reflecting the structural similarity among all OCT images; simultaneously constructing an association matrix representing the correspondence between OCT images and disease categories; and a model training module that introduces the structural similarity alignment matrix and association matrix as joint supervision signals into the objective function, adaptively learning to obtain an ophthalmic disease diagnostic model; the ophthalmic disease diagnostic model outputs a classification diagnostic result representing the probability that the input OCT image data belongs to various ophthalmic diseases. This invention achieves automatic identification and classification of ophthalmic diseases, with high diagnostic accuracy and good robustness.

The invention relates to the glasses industry, and aims to provide a lens structure for assisting eye disease rehabilitation by filtering and a manufacturing method thereof. A traditional lens is mainly used for correcting ametropia, and on the basis, by changing the filtering permeability of the lens, the filter lenses with different colors are used for filtering light rays with different wavelengths, the light rays act on fundus cells, the functions of the fundus cells are affected, and the effects of protection and auxiliary treatment of eye diseases are achieved. Yellow, tawny, gray, red and Finnish green filter lenses and sleep-aiding blue lenses (10%-30% of dyed lenses) are specifically designed. Lenses with different colors have unique filtering characteristics and can play a role in different eye diseases, for example, a light yellow lens is added to amblyopia to accelerate rehabilitation, and a brown lens is added to macular degeneration to suppress disease development. Meanwhile, the invention further provides a lens manufacturing method which comprises the steps of adding a color matching standard, carrying out standard operation on a dyeing heating process and the like, and the lens chromatic aberration is controlled in the horizontal direction so as to ensure the lens quality and the filtering effect.

Based on co-drugs representing two different chemical entities and the co- and sequential administration of the two chemical entities, novel therapies for macular degeneration and TTR amyloidosis are provided. The first component (“selective TTR ligand”) is a chemical entity that binds to TTR in the RBP4 (retinol-binding protein 4)-TTR (transthyretin) complex, which participates in the delivery of retinol to the retina. This component reduces retinol transport from circulation to the retina and provides stabilization of the TTR tetramer. The second component (“C20-D3-visual chromophore-generating compound”) is a C20-D3 modified retinoid or carotenoid that, when metabolized in mammals, ultimately produces a C20-D3 visual chromophore, which is presented in the retina as C20-D3-9-cis-retinal or C20-D3-11-cis-retinal. Deuteration at C20 reduces the formation of lipofuscin biretinol, but other functions (such as providing a precursor for the synthesis of the visual chromophore 11-cis-retinaldehyde in vivo) are not reduced.

The invention provides a nanoparticle penetrating cornea as well as a preparation method and application thereof. The nanoparticle comprises a cationic liposome G2-C14, an inner core formed by aliphatic polyester and an amphiphilic polymer, and a shell modified by polysaccharide, the hydrophobic drug and the siRNA are loaded in the inner core. According to the nano-particles provided by the invention, through polysaccharide surface modification, ocular surface adhesion and trans-epithelium transport capability are enhanced, multi-barrier penetration of the eye is realized, the nano-particles are effectively delivered to a focus area of posterior segment of the eye, the delivered siRNA targets to silence the expression of age-related macular degeneration pathogenic genes, and the hydrophobic drug removes active oxygen and inhibits release of inflammatory factors, so that the anti-aging effect of the nano-particles is improved. The focus thickness is synergistically reduced.

The application discloses a macular hole postoperative recovery effect classification method based on OCT images, and comprises the following steps: constructing an OCT image dataset, training and verifying a model; introducing an adaptive model authority coefficient for the differences in the judgment of different deep learning models, and performing model integrated decision support to classify the rehabilitation effect; performing model hyperparameter optimization and deep learning model training and verification; and using the trained deep learning model to classify the macular hole disease rehabilitation effect. The macular hole disease rehabilitation effect classification intelligent implementation method based on OCT images provides a computer-aided tool for clinicians, and can provide quantitative analysis result support for preoperative discussion.

The application discloses an AMD efficacy prediction method, system, device and medium based on feature fusion, belongs to the technical field of efficacy prediction, and comprises the following steps: acquiring optical coherence tomography image data and demographic characteristics of an age-related macular degeneration patient; determining deep learning features and imaging features according to the optical coherence tomography image data; performing feature selection based on the deep learning features, the imaging features and the demographic characteristics to obtain input features; performing calculation by combining a time series analysis network with the input features to determine a hidden state; and performing feature change trend analysis according to the hidden state to determine an age-related macular degeneration efficacy prediction result. The application proposes a multi-feature fusion long short-term memory network, and realizes efficacy prediction of anti-vascular endothelial growth factor treatment for the age-related macular degeneration patient.

The invention discloses application of cnidium lactone in preparation of a medicine for treating AMD or corneal injury, and belongs to the field of biological medicine. It is found for the first time that the cnidium lactone can inhibit sodium iodate induced retinal pigment epithelial cell injury, and it is also found for the first time that the cnidium lactone can promote injured cornea repair; based on the discovery, the invention respectively provides application of cnidium lactone in preparation of medicines for treating age-related macular degeneration and preparation of medicines for treating corneal injury. Experimental results show that cnidium lactone can remarkably reverse the retinal pigment epithelial cell degradation trend caused by age-related macular degeneration and can also remarkably promote corneal notch healing. The invention provides a new optional medicine for treating age-related macular degeneration and corneal injury, expands the application range of cnidium lactone, and has outstanding clinical practical value and wide application prospect.

The invention discloses an idiopathic macular pore patient postoperative retina change clinical observation method, which comprises the following steps: S1, collecting patient data, S2, carrying out an operation, S3, carrying out statistical analysis, S4, comparing data, and S5, concluding, and collecting 32 idiopathic macular pore patients to be included in the group for research. All patients are divided into two groups according to different operation modes, main observation indexes are central retina light sensitivity and peripheral retina light sensitivity, and other observation indexes comprise optimal corrected vision, retina superficial layer blood flow density, retina deep layer blood flow density and macular central depressed choroid thickness. The differences of the observation indexes between the two groups are compared, it is obtained through observation that after the idiopathic macular hole is treated through the vitreous body operation, the retina light sensitivity of the center of the macular part is obviously improved in the early stage of the operation, and improvement of the retina light sensitivity of the center of the macular part is closely related to changes of the retina blood flow density.

To provide a deep neural network framework for processing OCT images to predict treatment intensity.SOLUTION: Systems and methods relate to processing optical tomography coherence (OCT) images to predict characteristics of treatment to be administered to effectively treat age-related macular degeneration. The processing may include pre-processing the image by flattening and / or cropping the image (230), and processing the pre-processed image using a neural network (235). The neural network may include a deep convolutional neural network. An output of the neural network can indicate a predicted frequency and / or interval at which treatment (e.g., anti-vascular endothelial growth factor therapy) is to be administered so as to prevent leakage of vasculature in the eye (240).SELECTED DRAWING: Figure 2