718 results about "Retina" patented technology

The present application provides a method for diagnosing and / or evaluating the presence or absence, severity or degree of the improvement of a retinal disease in a subject, which comprises determining and / or evaluating circulatory parameters, retinal function, retina morphology and / or visual relating quality of life (QOL).

The invention relates to the technical field of additive manufacturing, and discloses an additive manufacturing lens surface optimization method based on real-time feedback control. The method comprises the following steps: firstly, acquiring eye biometric data and personalized visual demand parameters of a wearer, establishing a personalized optical model of eyeballs according to the eye biometric data and the personalized visual demand parameters, and deducing a retina defocusing amount distribution map; and determining spatial arrangement and geometric morphology parameters of the distributed out-of-focus microstructure layer on the lens according to the atlas. In the additive manufacturing process, the optical material is deposited and solidified layer by layer, and the three-dimensional shape information of the surface of the optical material is obtained in real time after deposition of each layer. And comparing and analyzing the morphology information with a theoretical model to generate a morphology deviation result. And then, a correction instruction of the printing parameters is calculated by using the correction model, and the printing parameters of the additive manufacturing equipment are adjusted in real time, so that real-time compensation and optimization of the morphology deviation are realized, and finally, a high-precision lens product meeting personalized optical design requirements is manufactured.

The invention discloses an OCT (Optical Coherence Tomography) retina image denoising method based on a high-frequency enhanced diffusion model, which is characterized in that a double-branch diffusion model network constructed based on frequency perception Fourier transform attention (FFTA) is used for separating different frequency domains, enhancing specific frequency domain features and fusing the specific frequency domain features into a spatial domain feature map to realize stronger frequency domain perception and processing capability; the invention relates to a time step T coding method for a module of frequency domain attention. The time step T of the diffusion model is used as a parameter to be coded into a frequency domain attention module to participate in self-attention matrix calculation, so that frequency domain feature processing is aligned with the iteration step number of the diffusion model, and different frequency domain information is pointedly processed at different time steps T; the frequency selective hopping mechanism uses pooling operation to obtain a high / low frequency characteristic pattern, so that the network has adaptive frequency domain retention capability for different local parts.

Various implementations disclosed herein include devices, systems, and methods that initiate an action based on a detected gaze direction oriented towards a target area (e.g., a hot corner / zone). For example, an example process may include producing a reflection by directing light towards an eye using an illuminator, receiving sensor data from a sensor, wherein a direction of sensing by the sensor (e.g., the optical axis of the camera) and a direction from the eye to a target area are approximately aligned, determining a reflective property (e.g., a spectral property) of the reflection based on the sensor data, detecting that a gaze direction of the eye is approximately oriented towards the target area (e.g., a hot zone / spot) based on the reflective property, and initiating an action based on detecting that the gaze direction is approximately oriented towards the target area.

The invention relates to the technical field of visual health management, in particular to a ciliary muscle adjustment training system and method based on eye movement tracking, and the method comprises the steps: collecting eye movement data of a fixation point track, an adjustment amplitude change rate and pupil response time in real time, and combining personalized parameters such as the age of a user, diopter and a training target; inputting a ciliary muscle training dynamic planning algorithm module, dynamically generating a stage scheme containing a training action type, a single-group duration, a stimulation interval and a focal length adjustment strategy, and adaptively adjusting the strategy according to real-time adjustment stability and a historical ability curve; through multi-dimensional matching analysis of a pre-stored standard eye movement template, a training specification score is calculated from the track goodness of fit, speed uniformity, amplitude standard-reaching rate and binocular coordination, visual fatigue parameters are obtained based on continuous training duration, pupil fluctuation and retina reflex change, a scoring result is dynamically corrected, and a visual fatigue evaluation result is obtained. Personalized, self-adaptive and quantitative safety control of the training process is realized.

The invention discloses an electric power meter intelligent reading system based on image recognition, and relates to the technical field of computer vision. The method is used for solving the problems of poor instrument reading stability and low range identification accuracy in a complex environment. The method comprises the following steps: firstly, performing multi-scale retina processing and four-direction gradient integral response analysis through an anti-shielding dial plate detection module, generating a probability heat map based on symmetry distribution, and outputting an accurate dial plate region segmentation mask through channel fusion; secondly, extracting a single-pixel wide pointer skeleton through non-maximum suppression and morphological refinement by using a meta-learning skeleton extraction module, and obtaining scale line distribution characteristics based on radial gradient analysis; thirdly, performing three-level progressive verification through a context range analysis module in combination with a geometrical relationship, a knowledge graph and a logical relationship, and outputting a range parameter; multi-dimensional information fusion is adopted to evaluate segmentation quality and skeleton integrity and verify consistency, reliable reading is generated, credibility evaluation is carried out, and high-precision stable reading in a complex environment is realized.

The invention discloses a multi-modal information fused high-myopia retina image classification method and system. The method comprises the following steps: acquiring an OCT image of a to-be-classified high-myopia retina and structured numerical data corresponding to the image; the OCT image is preprocessed, the preprocessed image is input into an image encoder for high-dimensional semantic representation learning, and overall semantic vector representation of the image is obtained; converting the structured numerical data into a medical language description text, and inputting the medical language description text into a text encoder for deep semantic modeling to obtain overall semantic vector representation of the text; inputting to a multi-modal fusion module, carrying out feature interaction and fusion through a bidirectional cross attention mechanism, and generating a fused multi-modal feature; and outputting a retina splitting stage category corresponding to the OCT image through a classification module. According to the method, the OCT image, the structured numerical data and the split staging definition text are utilized to perform multi-modal feature fusion, so that the accuracy of image staging recognition is improved.

A computer-implemented system and method for pupil-directed retinal projection in near-eye displays are disclosed. The computer-implemented system provides smart glasses with directed physical pixels that project light beams / signals directly onto user's retina based on pupil position and size. The glasses comprise frame, lenses with directed pixel layers, sensors for tracking pupil movement. Each directed pixel generates multiple virtual pixels by rapidly changing its emission angle. Each directed pixel with pupil's real-time tracking, provides automatic adjustments to virtual contents, ensuring accurate alignment of images with field of view of users while identifying vergence-accommodation conflict. The glasses function as prescription lenses, virtual reality displays, augmented reality devices without traditional optical systems. Additional features include depth sensors, cameras, connectivity to peripheral devices. The glasses enable seamless blend of virtual and real-world experiences, creating immersive “Mixverse” environment. Various input methods, including gesture recognition and brain-computer interfaces, allow for intuitive control and interaction.

The invention discloses a medical image analysis method and system based on a visual language model, and belongs to the technical field of medical image intelligent diagnosis, and the system comprises an image preprocessing unit which carries out the down-sampling of an original retina OCT image to 256 * 256 and carries out the normalization of the original retina OCT image; the feature encoding unit comprises an image encoder based on RET Found in combination with LoRA optimization and a text encoder based on BioClinicalBERT; the class balance comparison learning unit is used for adjusting loss through class balance coefficients so as to relieve the class imbalance problem; the uncertainty estimation unit is used for calculating confidence quality and uncertainty scores based on Dirichlet distribution, and determining a threshold value in combination with an improved Youden index; and the model training unit adopts a total loss function of class balance loss and uncertainty loss, outputs a diagnosis result and an uncertainty score through transfer learning, and further comprises an image input module, a result display module and a data storage module. Rare disease classification performance and reliability are improved, training efficiency is improved through LoRA optimization, and an accurate and reliable scheme is provided for detection of the rare retina diseases.

A system for hypertensive retinopathy (HTNR) detection includes a processor and a memory, including instructions stored thereon, which when executed by the processor, cause the system to: preprocess a retinal image using contrast enhancement, noise reduction and / or resolution normalization; segment a plurality of vessels from the preprocessed retinal image to generate a vessel segmentation map; detect a retinal marker, a vascular marker and / or an optic disc marker in the preprocessed retinal image using a first machine learning model; generate a severity score based on the detections; determine that the severity score exceeds a predefined threshold; and generate an output indicating a presence of HTNR based on the vessel segmentation map and the severity score using a second machine learning model.

The invention discloses a multi-point defocus management method for intelligent training glasses, and particularly relates to the technical field of defocus management, and the method comprises the following steps: S1, data collection; s2, scene recognition and intention judgment; s3, generating a dynamic defocusing scheme; s4, performing out-of-focus stimulation presentation; and S5, performing effect evaluation and adaptive adjustment. Original isolated eye movement tracking, scene recognition and adjustable optical technologies are organically connected in series through an intelligent decision-making core, an autonomous system capable of managing defocus like automatic driving is formed, the fundamental pain point that a traditional technology is static and rigid and cannot adapt to the dynamic requirement of a user is solved, and the user experience is improved. According to the invention, qualitative change of defocus stimulation from fixing to following is realized, it is ensured that the defocus stimulation can continuously and accurately act on the most critical area of the retina, meanwhile, the definition of the central view is ensured to the maximum extent, the contradiction between the defocus effect and the visual comfort is solved, and accurate intervention is realized.

A lens element intended to be worn in front of an eye of a wearer, the lens element comprising:-a holder, and-a plurality of optical elements superimposed on the holder, each optical element simultaneously provides a first optical function based on a prescription of the wearer for correcting refractive abnormalities of the eye and a second optical function that does not focus an image on the retina of the eye, characterized in that each optical element comprises a central region and a plurality of outer regions surrounding the central region, a maximum height of the central region is smaller than a maximum height of the outer region.

The invention provides a large-view-field high-resolution compound eye camera array system based on bionic human eye vision. The system is composed of a curved surface support and an industrial camera array arranged on the curved surface support. Reverse extension lines of optical axes of all the cameras intersect at the same point to form a concave surface structure similar to the retina, and the fixed view field overlapping rate of the adjacent cameras is kept. The industrial camera array is used for collecting a target scene image, large-view-field information is obtained by fusing and splicing all camera images, and a high-resolution image is obtained by conducting super-resolution reconstruction on a plurality of related images in a view field center interested area. The system provides three working modes, namely a low-resolution mode, a conventional-resolution mode and a super-resolution mode, which can be switched by adjusting camera parameters. Finally, the system can perceive the dynamic change of the edge of the field of view in a high-frame-rate and low-resolution mode, magnify the details in the center of the field of view in a super-resolution mode, realize efficient non-uniform imaging, and optimize the information acquisition and processing efficiency and the structure compactness.

The invention discloses a structure perception mask reconstruction learning system and method for OCT image segmentation, and belongs to the technical field of image processing. According to the system, in a pre-training stage, an encoder fused with ViT-Base and a multi-expert self-adaptive reconstruction module is utilized to perform mask reconstruction on a label-free OCT image. In the pre-training stage, two-stage training is performed through a random mask strategy and an attention-guided dynamic mask strategy, so that an encoder-decoder can be transited from random learning to focusing on a structural key area, and optimization is performed by combining a structural perception loss function, thereby forcing a model to learn fine boundary and texture information of a retina. After training is completed, an encoder which learns rich structure knowledge serves as a backbone network to be migrated and is combined with a segmentation decoder of a downstream task, fine adjustment is carried out on a small amount of annotation data, and the accuracy of downstream segmentation is remarkably improved.

For see-through AR displays, the current state of art uses geometric correction to lower the display location error, however this is far from an ideal solution and requires knowing range or pose of the devices. A dual-function optic for eye display & camera is disclosed, wherein a sensor camera imaging optics pipeline with a virtual projection point at an eye's retina reduces parallax errors to zero.

The invention discloses a retina OCT (Optical Coherence Tomography) image denoising method based on zero sample learning. The method comprises the following steps: generating a noise independent image pair for a single noisy image by adopting a CDIS (Coherent Discrete Identifier) The method comprises the following steps of: carrying out de-noising by using an MLFSnet network (AF-MSDSConv, Aap-LSM, SA, a reconstruction module); using RMSE symmetry and consistency joint loss zero sample training; in the reasoning stage, an original image is directly input, and a same-resolution de-noising result is output. The speckle noise can be significantly suppressed and the layered structure of the retina can be retained without noise-free true values or pairwise data, so that the retina can be used while being shot.

The invention discloses a scattering lens and a design method thereof, which are applied to the technical field of optical devices and visual correction, and aims to solve the technical contradiction that the traditional myopia control lens is difficult to give consideration to the central visual definition and the effective intervention of peripheral retina. Unit density, size and scattering angle are configured in a differentiated manner, and optical artifacts are suppressed by adopting aperiodic arrangement; a pupil adaptive modulation layer and a task mode switching module are combined to realize dynamic response of illumination and vision tasks; in design, based on individual physiological parameter reverse optimization, a multi-target genetic algorithm is adopted for iterative calibration, the peripheral retina contrast regulation and control efficiency is remarkably improved by more than three times, meanwhile, it is guaranteed that the contrast loss of a central area is lower than 5%, and the high-precision, personalized and all-weather myopia control effect is achieved.

The invention discloses a retina fundus image generation method based on a diffusion model. Firstly, a training data set and a regularization data set are constructed; then, constructing a diffusion model which comprises a variational auto-encoder, a U-Net denoising network and a text encoder; the variational auto-encoder comprises a variational encoder and a variational decoder, and the U-Net denoising network is embedded between the variational encoder and the variational decoder; the structured text prompt passes through a text encoder to obtain a text embedding vector, and the vector is injected into the U-Net denoising network as condition information; the variational encoder compresses the retina fundus image into potential features, the U-Net denoising network carries out denoising on the potential features under the guidance of condition information, and the denoised potential features are reconstructed into a high-resolution retina fundus image through the variational encoder; and finally, generating a retina fundus image based on the pre-trained diffusion model. The controllability of image generation is improved, and the generated image is highly consistent between the focus form and the medical description.

A surgically implanted ocular optical array that can be used in both therapeutic and diagnostic applications is described. A device configured to be implanted in an eye includes: an imaging system that receives visible light incoming to the eye; optical source generating circuitry that generates an optical signal based on the light received by the imaging system; and an optical phased array (OPA) that generates and projects an image onto a retina of the eye in which the device is implanted, the image being based on the optical signal generated by the optical source generating circuitry.

A retinal projection display system includes at least one visible light source for projecting a visible light image, an infrared light source for projecting infrared light, a scanning mirror having a field of view larger than the visible light image, a reflective surface on which the visible light image is projected and on which the infrared light is reflected at least partially towards an eye of a user, wherein the reflective surface is larger than the visible light image, at least one infrared photodetector for receiving reflected infrared light that reflects off of the eye of the user, and a hardware computation module comprising a processor and a memory, the hardware computation module configured to determine a gaze direction of the user based at least in part on the reflected infrared light.

Deep learning methods and systems for detecting biomarkers within optical coherence tomography volumes using such deep learning methods and systems are provided. Embodiments predict the presence or absence of clinically useful biomarkers in OCT images using deep neural networks. The lack of available training data for canonical deep learning approaches is overcome in embodiments by leveraging a large external dataset consisting of foveal scans using transfer learning. Embodiments represent the three-dimensional OCT volume by “tiling” each slice into a single two dimensional image, and adding an additional component to encourage the network to consider local spatial structure. Methods and systems, according to embodiments are able to identify the presence or absence of AMD-related biomarkers on par with clinicians. Beyond identifying biomarkers, additional models could be trained, according to embodiments, to predict the progression of these biomarkers over time.

Disclosed techniques evaluate the visual field of a patient's eye using deep learning techniques. A computer system obtains a plurality of cross-sectional scan images of a retina captured by an optical coherence tomography (OCT) device. The retina has an inner retinal layer. A retinal optical texture analysis (ROTA) map of the inner retinal layer is generated from the plurality of cross-sectional scan images. The ROTA map includes a plurality of pixels, and each pixel of the ROTA map corresponds to a respective optical texture signature value S providing information about tissue composition and optical density of the inner retinal layer at a respective retinal location. The computer system applies a machine learning model to process the ROTA map of the inner retinal layer to determine visual field sensitivity of the retina.

Embodiments disclose systems and methods that aid in screening, diagnosis and / or monitoring of medical conditions. The systems and methods may allow, for example, for automated identification and localization of lesions and other anatomical structures from medical data obtained from medical imaging devices, computation of image-based biomarkers including quantification of dynamics of lesions, and / or integration with telemedicine services, programs, or software.

Approaches are described for facilitating remote ophthalmic examinations using three-dimensional (3D) imaging and mixed reality technology. A system obtains real-time or stored 3D data of a patient's eye, capturing detailed anatomical structures. The system analyzes the 3D data to identify specific regions of the eye, such as the cornea or retina, and retrieves corresponding diagnostic data and patient-specific clinical information. The 3D data, diagnostic metrics, and clinical records are integrated to generate an interactive visualization, which is presented through a mixed reality interface. The system allows healthcare professionals to manipulate diagnostic overlays, investigate flagged abnormalities, and adjust the visualization using gesture-based inputs. Machine learning models may be applied to detect potential abnormalities in the eye, while the system also determines stages of the examination based on changes in the anatomical structure of the eye.

The invention belongs to the technical field of medical instruments, and particularly relates to a pair of hyperopia correction glasses based on a refractive topographic map and a design method thereof. The pair of hyperopia correction glasses comprises a base lens, the middle part of the base lens is an out-of-focus-free area, an annular area outside the out-of-focus-free area is an out-of-focus stimulation area, the geometric center of the out-of-focus stimulation area coincides with the center of the out-of-focus-free area, and a plurality of out-of-focus correction areas are arranged on the base lens within the out-of-focus stimulation area. And a plurality of micro lenses with the same diopter are arranged in each defocus correction area. Based on the MRT peripheral defocus detection result of the patient, the individualized full-eye customization technology is adopted, accurate matching of the lens and the peripheral defocus of the retina is ensured, the defocus amount of eyeballs in different directions can be accurately adjusted through individualized customization, the eyeballs return to a comfortable area, the ideal hyperopia defocus state is formed, and the visual effect of the eyeballs is improved. The effects of promoting eye axis growth and treating hyperopia are enhanced.

A chamber houses a camera, light sources, and an onboard computer. The camera may be an infrared camera. Infrared light source fibers feed into a circumferential adapter ring to illuminate the inside of the eye (retina). The adapter ring contains a central opening through which it fits around the camera lens. The adapter ring contains openings along the circumference for infrared fibers to provide a light source. Another light source is provided for illumination of the external surface of the eye adjacent to the camera.

The invention belongs to the technical field of femtosecond laser processing, and particularly relates to a femtosecond laser-based surface bulging out-of-focus lens processing method, which is used for processing a micro-lens array with the out-of-focus amount continuously changing from the eye side to the temporal side based on a plurality of bulging units. The cavity structure is machined below the bulging unit based on multiple laser control, the cavity structure provides a preset transformation foundation for subsequent secondary machining, the bulging unit is conveniently converted into a micropore structure, and after conversion is completed, the light transmittance does not obviously change. Under the condition that the light transmittance meets the requirement, the vision correction defocus lens which better meets the requirement for the real defocus amount of the retina and can prolong the service cycle after secondary processing is achieved.

One aspect of the present disclosure relates to an optical coherence tomography apparatus for imaging a patient's eye, more particularly to a sweep-source optical coherence tomography apparatus, the apparatus comprising a light source configured to generate a light beam, the light beam being distributed to a two-dimensional region on the patient's retina, and a camera equipped with a 2-D sensor, the apparatus being configured to bundle a plurality of pixels on the sensor such that each data point includes a composite response from a plurality of bundled pixels.

The invention discloses a fundus imaging system, which includes an optical path folding lens set, a virtual reality display, visible light fixation lamps, an illumination module, an image sensor, and a processor. The virtual reality display and the human eye are located on different sides of the optical path folding lens set. The virtual reality display forms images on the retina of the fundus of the human eye through the optical path folding lens set. The visible light fixation lamps are sequentially turned on to guide the eyeball of the human eye to rotate. When the visible light fixation lamp is turned on, the illumination module emits illumination light through the optical path folding lens set to illuminate the retina. The retina reflects the illumination light to form fundus light. The image sensor receives fundus light through the optical path folding lens set to form a sub-fundus image. The processor stitches all sub-fundus images into a full-fundus image and drives the virtual reality display to display the full fundus image.

The invention discloses a vehicle-mounted augmented reality head-up display (AR-HUD) self-adaptive display adjusting system and method based on retina perception. The system comprises a retina perception parameter extraction module, a driving instruction response analysis module, a display light environment acquisition analysis module and a dynamic adaptive display optimization module. The method comprises the following steps: acquiring a retina perception threshold value of a user through a contrast sensitivity test before driving, extracting objective physiological parameters such as pupil diameter, blinking rate and fixation stability in a preset time window during driving, and calculating a comprehensive fatigue index F; a display area brightness distribution model is established in combination with vehicle-mounted light sensor data, F-based adaptive adjustment and safe amplitude limiting are performed on the brightness and contrast of an AR-HUD image, it is ensured that key information reaches the lowest recognizable contrast threshold, and an over-bright area is restrained. Compared with a fixed display adjusting scheme, the information readability can be improved in different light environments, the subjective fatigue score can be reduced, and the vehicle-mounted augmented reality head-up display adaptability and watching comfort can be improved.