122 results about "Strabismus" patented technology

The invention relates to the technical field of marine remote sensing observation, in particular to a squint ATI-SAR multi-view sub-aperture focusing marine vector flow inversion method. The method comprises the following steps of observation of strabismus ATI-SAR loads, focusing of multi-view sub-apertures, inversion of multi-view HLOS flow velocity, overdetermined equation solving of vector flow and checking of internal and external consistency of the vector flow. Non-side-looking observation is adopted for the load, observability of components in the rail direction is enhanced through physical squint, and low cost of a single beam and system conciseness are kept; according to the method, the contribution of the azimuth component is in direct proportion to the squint angle sine, so that the along-track component far greater than the virtual squint can be obtained, the solvability of the equation is improved, and the inversion instability is reduced; visual and reliable information observation is achieved with small system burden, equipment investment is saved, large-scale vector flow on-orbit observation can be achieved, and engineering is easy to achieve. According to the method, three-step closed-loop processing is carried out, the bottleneck of the traditional technology is solved, and the engineering availability and the result robustness are broken through.

The invention discloses a strabismus detection method based on causal feature gating, and the method comprises the steps: carrying out the modeling analysis of a causal relationship between a key point coordinate and a strabismus category through a causal discovery algorithm, obtaining a causal relationship model used for determining the causal relationship, screening the key point coordinate based on the causal relationship model, and obtaining a strabismus detection result. Extracting a plurality of causal variables from a plurality of samples of the training sample set according to the causal variable set; and introducing a causal feature gating module between adjacent network layers of the classification model, training the classification model by using a plurality of causal variables, and performing adaptive adjustment on gating parameters in the training process of the classification model until the classification model converges or reaches a preset training round number, thereby obtaining a final classification model. According to the embodiment of the invention, the accuracy of strabismus classification can be improved, and the interpretability and medical application value of the model can be remarkably enhanced.

The invention discloses a causal feature selection-based graph neural network refined strabismus diagnosis method, system and device and a medium, and the method comprises the steps: obtaining nine face photos of a patient, and carrying out the image preprocessing of the nine face photos, so as to construct a nine-eye bitmap; detecting an orbit part of each eye position in the nine-eye-position map by adopting a target detection algorithm so as to extract a characteristic variable related to strabismus refined diagnosis in each eye position; a causal feature selection algorithm is adopted to screen out key feature variables having a direct causal relationship with strabismus refined diagnosis from the feature variables related to each eye position; and inputting the key feature variable of each eye position into a graph neural convolutional network model, and carrying out training optimization in a strabismus disease data set through a propagation formula to output a refined diagnosis result. According to the method, irrelevant details on the whole face image are removed to extract main eye areas to construct the nine-eye bitmap, so that the calculation cost is reduced; the key feature variable of each eye position is extracted by adopting a causal feature algorithm, and the key feature variable of each eye position is learned through the graph neural convolutional network model, so that the graph neural convolutional network model is more interpretable, and refined strabismus diagnosis is realized.

The utility model relates to the technical field of visual training, and discloses a strabismus correction training device which comprises a placing base, a swinging mounting cross rod is arranged above the placing base, a folding rod is further arranged above the mounting cross rod, the folding rod is of a hollow structure, a sliding telescopic rod is inserted into the folding rod, and the telescopic rod is arranged above the placing base. The size of the telescopic rod is completely matched with the size of the interior of the folding rod, and a second positioning rotary knob is installed on the outer portion of the end, corresponding to the telescopic rod, of the driving folding rod. The unfolding angle of the folding rod is adjusted through the bolt outside the installation cross rod to adapt to a user, then the observation plate and the picture album plate which need to be used are installed for use, the unfolding height can be flexibly adjusted when the device is used, the whole device can be folded and stored when the device is not used, and the occupied space of the whole device is reduced; and the use convenience of the device is greatly improved.

The present application relates to a strabismus detection method, a strabismus detection device and a wearable device. Among them, the strabismus detection method includes: obtaining the eye movement fluctuation information of each eye of a detection object based on a first detection rule; when the eye movement fluctuation information of each eye of the detection object is lower than a first threshold, obtaining the first eye movement information of each eye of the detection object when performing strabismus detection based on the first detection rule; wherein, the eye movement fluctuation information and the first eye movement information are associated with the change between the mean values of the eye movement direction vectors of the eyes during each eye movement plateau period when performing strabismus detection based on the first detection rule; when the first eye movement information of any eye is greater than a second threshold, it is determined that the detection object has an eye position deviation. It realizes an objective and unified eye position deviation measurement process and improves the efficiency of strabismus detection.

The invention discloses a strabismus detection method, device, system and equipment based on display equipment and a medium, and the method comprises the steps: calibrating a detection position of a user based on a reference marker worn by the user, and determining that the user is located at a target detection position; in the detection process, in response to a detection control instruction, the display device is controlled to display a target image corresponding to the uncovered eye, and the target image is matched with the covering unit to form a covering effect on the covered eye and display a target sighting mark visible to the uncovered eye; controlling an image acquisition device to acquire a change condition of converting the uncovered eye from the covered state to the uncovered state; and based on the change condition that the uncovered eye is converted from the covered state to the uncovered state, determining the deflection data corresponding to the uncovered eye, thereby providing an implementation condition which can be widely applied for strabismus screening, reducing the difficulty of strabismus detection, and improving the accuracy and reliability of strabismus detection under the guidance of a non-physician.

The invention relates to a pair of comprehensive myopia and strabismus prevention and control glasses with an electric control dimming film, the reverse electric control dimming film is most power-saving and practical, and a glasses control system mainly comprises a battery, a remote controller, a control unit, the electric control dimming film, an APP control module and the like. The switching between the atomization state and the transparent state of the control units in the two glasses legs is controlled through a remote controller or an APP, so that the myopia and strabismus adjusting ability of eyes and the vision of strabismus eyes are exercised.

The utility model provides a pediatric strabismus auxiliary correction device, including: a rod body, the rod body includes a connecting piece, a first rod body, a second rod body and a third rod body, the first rod body, the second rod body and the third rod body are connected in series in sequence through the connecting piece; the first rod body, the second rod body and the third rod body form a folding structure through the connecting piece; a sphere, the first rod body, the second rod body and the third rod body are all provided with a magnetic seat, the sphere is connected to the magnetic seat by magnetic attraction and adsorption; when the device is used, the first rod body, the second rod body and the third rod body are mutually threadedly connected to form an integral structure, and the sphere array is distributed on the rod body. The utility model can also mutually thread the first rod body, several groups of second rod bodies and the third rod body to form a whole, improve the stability of the structure, avoid up and down floating like the soft rope structure, and improve the training effect.

The invention provides an artificial intelligence-based strabismus prevention method and system. The method comprises the following steps: S1, acquiring a face video stream in an object viewing process of a user through a camera; s2, extracting each frame from the face video stream, and identifying a plurality of user face feature points in each frame; s3, selecting facial key points related to strabismus from the facial feature points of the user, and statically identifying a strabismus trend according to the facial key points; s4, according to the face key points, dynamic detection of the strabismus trend is carried out, and the dynamic detection comprises head three-dimensional posture detection and binocular movement coordination detection; and S5, according to the static identification and dynamic detection results, performing intervention on the user by adopting a three-level intervention strategy to realize accurate prevention and control of the strabismus behavior. The method can effectively prevent strabismus.

1. The name of this design product: Optometrist Workbench (Jianlan AI+). 2. Application of this product design: Used for various visual function tests, comprehensive analysis and equipment management such as myopia, hyperopia, strabismus and amblyopia. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the key points of the design: Main view of component 1. 5. Other circumstances that require explanation: This design product includes component 1 and component 2.

The invention provides a high strabismus imaging method and system for cooperative scanning of an agile attitude and a load. The method comprises the following steps: calculating optimal imaging parameters of a high strabismus mode; establishing a load high-squint stripe imaging method under satellite level flight and left and right side-looking attitudes; establishing an SAR imaging coordinate system in a posture and load cooperative scanning state; establishing an attitude agile maneuvering and load electric scanning coordinated slip aggregation mode implementation method; and establishing an azimuth large squint multi-target mode observation mode. According to the invention, the agile maneuvering capability of the satellite platform and the large-angle scanning capability of the load phased-array antenna are fully utilized, and the agile maneuvering capability of the satellite platform and the large-angle scanning capability of the load phased-array antenna cooperate to realize in-orbit large-squint imaging, so that the method has popularization and practical values for improving the in-orbit application efficiency of light and small

The present application discloses a strabismus detection method, apparatus and system based on a display device, a device, and a medium. The method comprises: calibrating a detection position of a user on the basis of a reference marker worn by the user, and determining that the user is at a target detection position; in the detection process, in response to a detection control instruction, controlling a display device to display a target image corresponding to an uncovered eye, wherein the target image works in conjunction with a covering unit to achieve a covering effect on the covered eye and display a target optotype visible to the uncovered eye, and controlling an image collection apparatus to collect the change of the uncovered eye being converted from a covered state to an uncovered state; and on the basis of the change of the uncovered eye being converted from the covered state to the uncovered state, determining deviation data corresponding to the uncovered eye. Widely applicable implementation conditions are provided for strabismus screening, so that the difficulty of strabismus detection is reduced, thereby improving the accuracy and reliability of strabismus detection under the guidance of a non-physician.

The invention provides a strabismus measuring instrument eye shielding intelligent adjusting method. The method comprises the steps that a first face image is acquired, and the first position and size of an eye area are determined; obtaining a size ratio of a preset measurement window to the face image, and controlling the measurement window to form a shielding area according to the size ratio and the first position and size of the eye area; and controlling the occlusion area to perform brightness change according to a preset occlusion strategy. According to the invention, shielding areas with proper sizes can be dynamically formed at the left eye and the right eye, a shielding effect is formed according to a preset shielding strategy, and the movement and the second position state of the shielded eyeballs can be captured through a specific camera; therefore, the strabismus degree of the user is accurately calculated by calculating the relative value of the second position state and the first position state.

The present invention provides a strabismus training device, which is characterized by comprising a display module; an image capturing and processing module; a calibration module; an eye movement point calculation module; and a strabismus training prism diopter range calculation module. The beneficial effects of the present invention are as follows: on the basis of maintaining binocular fusion vision, by performing visual training on strabismus patients, the strabismus degree is gradually reduced, achieving the effect of treating strabismus without surgery.

The application discloses a strabismus detection method based on a causal feature gate, comprising: modeling and analyzing the causal relationship between key point coordinates and strabismus categories by using a causal discovery algorithm to obtain a causal relationship model for determining the causal relationship, screening the key point coordinates based on the causal relationship model to obtain a causal variable set, and extracting a plurality of causal variables from a plurality of samples in a training sample set according to the causal variable set; introducing a causal feature gate module between adjacent network layers of a classification model, training the classification model by using the plurality of causal variables, and simultaneously adaptively adjusting gate parameters in the training process of the classification model until the classification model converges or a preset training number of rounds is reached to obtain a final classification model. The application embodiment can not only improve the accuracy of strabismus classification, but also significantly enhance the explainability and medical application value of the model.

To provide a perspective inspection instrument 1 that is capable of accurately measuring a fusion maintenance capacity and that enables reduction in size and weight.SOLUTION: The perspective inspection instrument 1 includes a hand-held body 2. The body 2 includes: a window part 3 in which two light-transmitting members 8 and 9 are arranged to be overlapped; and a variable mechanism 11 that cooperates with the two light-transmitting members 8 and 9 to continuously vary the transmittance of light transmitted through the window part 3.SELECTED DRAWING: Figure 2

The invention relates to the technical field of endoscopes, and discloses a strabismus endoscope, an assembling method thereof and an endoscope system.The strabismus endoscope comprises an insertion part, the insertion part comprises a tip part, the tip part comprises a main body part, and the main body part comprises a mounting surface used for mounting a camera shooting unit and a lighting unit; the main body part comprises two mounting cavities, the mounting cavities comprise a first cavity and a second cavity, the first cavity is used for mounting the camera shooting unit or the lighting unit, the first cavity is provided with a first opening, the second cavity is provided with a second opening, and the camera shooting unit or the lighting unit can be mounted in the second cavity through the second opening and continuously mounted in the first cavity through the second cavity. According to the strabismus endoscope, the assembling method of the strabismus endoscope and the endoscope system, the problems that in the prior art, when the camera shooting unit and the lighting unit are installed in the tip part, operation is inconvenient, and the tip part is not prone to being decontaminated can be solved.

The present specification discloses a method and an apparatus for generating strabismus angle information. The method for generating strabismus angle information according to the present specification may involve: receiving image data, captured of an optotype, from an RGB camera as input, and calculating coordinates for the optotype; storing a plurality of measurement values, for the gaze direction of an eyeball having an open field of view, from an eyeball tracking sensor; storing the timing at which one eyeball having an open field of view gazes at the optotype; and calculating the strabismus angle of a subject for each eyeball from the depth sensor by using information about the distance between the subject and the optotype, the timing information, and the gaze tracking information.

The invention relates to the technical field of vision detection, in particular to an eye position image analysis system for measuring a strabismus angle of a child. The strabismus measurement reliability is determined based on the difference of position changes of different types of pupil center areas in eye position images of two steering eye positions in a symmetrical eye position pair and the difference of the position relations between the pupil center areas and cornea light reflecting spots in the eye position images; the strabismus measurement reliability is adjusted through the included angle between the steering eye position and the orthogonal direction in all symmetrical eye position centering, the strabismus deviation angle is determined, and then the overall measurement reliability is determined; determining a strabismus measurement value according to the difference of position changes of different types of pupil center areas in the eye position images of the steering eye position and the positive eye position; and adjusting the strabismus measurement value by using the overall measurement reliability of all the steering eye positions, and determining the final strabismus angle under the positive eye position. According to the method, the final strabismus angle is determined by integrating the information of all the steering eye positions, and the dynamic characteristics of intermittent strabismus are effectively captured.

The invention discloses an RFPA four-dimensional professional examination method, which comprises a first examination module (referred to as R for short) for examining monocular and binocular near and far vision of a patient in a natural state to obtain a first examination result; the second examination module (Fusion for short) is used for examining the far and near image fusion condition of the patient according to the first examination result to obtain a second examination result; and the third examination module (Phoria for short) is used for examining the far and near eye position conditions of the patient according to the second examination result to obtain a third examination result. The method is reasonable in design, the simple visual function four-step inspection method is used, the situations and problems of the eye ametropia problem, the image fusion function problem, the strabismus and adjusting function of a patient can be rapidly and accurately inspected, and a basis is provided for accurately correcting the visual abnormality problem of the patient.

The invention provides a strabismus screening system based on multi-dimensional dynamic eye movement tracking. The strabismus screening system comprises a data acquisition module, a data preprocessing module, a data analysis module and a result feedback module. A cartoon experimental normal form is adopted for an experiment through a domestic Pupil.IO AIO eye tracker, so that the eye movement track is monitored, the stability of a fixation point is dynamically quantified, the dynamic change during jump reaction is captured, multi-dimensional eye movement feature calculation such as sight line difference analysis is carried out, and finally dichotomy result judgment is carried out. The problems of inherent limitation, high equipment price, insufficient clinical suitability of a data analysis model and lack of a standardized process of a traditional inspection method are effectively solved.

A fine-grained strabismus diagnosis method and system using a graph neural network based on causal feature selection, and a device and a medium. The method comprises: acquiring nine facial photographs of a patient, and performing image preprocessing on each of the nine facial photographs, in order to construct a nine-gaze-position image; using an object detection algorithm to detect an orbital region in each gaze position in the nine-gaze-position image, in order to extract feature variables of each gaze position that are related to fine-grained strabismus diagnosis; using a causal feature selection algorithm to select from among the feature variables related to each gaze position key feature variables having a direct causal relationship with fine-grained strabismus diagnosis; and inputting the key feature variables of each gaze position into a graph neural convolutional network model, and performing training and optimization with a strabismus disease dataset by means of a propagation formula, in order to output a fine-grained diagnosis result. Unrelated details are removed from entire facial images, and main eye regions are extracted to construct a nine-gaze-position image, thereby reducing the computational cost; and a causal feature algorithm is used to extract key feature variables of each gaze position, and a graph neural convolutional network model is used to learn the key feature variables of each gaze position, thereby making the graph neural convolutional network model more interpretable, and thus realizing fine-grained strabismus diagnosis.

A method, apparatus, and program product for dynamically correcting vision of a user utilizing pass-through augmented reality goggles comprising orientation sensors associated with eyes of a user, a camera configured to capture surroundings of the user, and at least one display aligned with each respective eye, the at least one display is configured to render a computer-generated image of the surroundings of the user. A processor is configured to perform the steps of: detecting gaze vectors associated with the eyes, obtaining respective magnitudes of ocular misalignment of the eyes, capturing at least one image of the surroundings of the user, generating a computer-generated image of the surroundings of the user based on: the at least one image of the surroundings of the user; the gaze vectors of the eyes, and the magnitude of ocular misalignment of the eyes. The processor is further configured to perform the steps of rendering for each display an adjusted first computer-generated image of the surroundings of the user.

The invention discloses amblyopia and strabismus recovery training equipment and system, and the method comprises the steps: collecting a face image of a user through a camera, extracting face key feature points from the face image of the user through employing an image analysis and processing technology based on machine vision, and calculating the head posture data of the user; performing data normalization on the head posture data of the user for embedded coding, and performing facial feature extraction and enhancement on the facial image of the user at the same time; therefore, adaptive adjustment of the distance between two identical object images and the display angle of the object images is realized based on cross-modal intersection prompt joint representation between enhanced user facial features and user head posture embedding features. Through the mode, the normal eye position interpupillary distance and the head posture of the user can be matched more accurately, the object image distance and the display angle can be adjusted in real time, manual intervention of the user is not needed, and therefore it is ensured that training parameters are consistent with actual requirements of the user, and the effect of amblyopia and strabismus recovery training is effectively improved.

The invention belongs to the technical field of eye detection, and provides an eye position image acquisition and management method and system. The method comprises the following steps: grouping eyeball rotation images according to eyeball directions; predicting a first key parameter based on the illness state record data of the user and each historical eyeball rotation image corresponding to any orientation, and extracting a second key parameter from each eyeball rotation image grouped in the same orientation; target eyeball rotation images are screened from the groups, third key parameters of eyeballs are extracted from the target eyeball rotation images, all the target eyeball rotation images are synthesized into a panoramic image according to the directions corresponding to the groups to which the target eyeball rotation images belong, and the panoramic image and the third key parameters are stored in an associated mode. According to the method, the eye position image of the user and the corresponding eye feature parameters can be automatically collected, the data stored in an associated mode can be conveniently subjected to analysis such as current strabismus detection and screening and subsequent contrastive analysis of the recovery degree, and the strabismus condition analysis efficiency can be remarkably improved.

The application relates to the technical field of knowledge graph, and particularly provides a strabismus three-dimensional mapping method and system based on a knowledge graph, which comprises the following steps: taking a starting point space coordinate, a patient corneal reflection point offset and an eyeball rotation center coordinate as attribute values of an entity node, establishing a directed connection edge between nodes according to a fixed attachment relationship between muscles and eyeballs and between muscles and bone walls in anatomy, and constructing an initial heterogeneous graph by all entity nodes and the directed connection edge; weighting and aggregating attribute values of neighborhood nodes connected by the directed connection edge of each node in the obtained initial heterogeneous graph to obtain an aggregated feature vector of the node; and mapping all node coordinates in each obtained sub-graph to a unified three-dimensional coordinate system, and adjusting the relative positions between the sub-graphs so that all positioning base points are located on a plane. The application realizes systematic mapping and pathological posture analysis of three-dimensional space configurations of eye external muscles of a strabismus patient.

A system for strabismus assessment and a method of strabismus assessment. The system comprises a display module arranged to display a visual stimulus to be observed by an observer; an image capturing module arranged to record a plurality of images of at least one eye of the observer observing the visual stimulus; and a processing module arranged to determine an ocular misalignment condition of the observer based on the plurality of images recorded by the image capturing module.

The invention discloses a refined strabismus diagnosis method, system and device based on a hierarchical decoupling attention mechanism and a medium, and the method comprises the steps: obtaining nine face pictures of a patient, and carrying out the image preprocessing of the nine face pictures, so as to construct a nine-eye bitmap; after dividing the nine-eye bitmap to form a plurality of blocks of the same size, mapping the plurality of blocks into a plurality of corresponding block inserts, and performing position coding on the plurality of block inserts to form a nine-eye bitmap representation map; sequentially extracting intraocular detail features and interocular change features in the nine-eye representation diagram by adopting local multi-head attention, and rearranging the intraocular detail features and the interocular change features to form a refined representation diagram; and performing global pooling on the refined representation diagram to form a global descriptor, and performing training optimization on the global descriptor input into the hierarchical classifier by adopting a combined loss function to output a refined diagnosis result. According to the method, detail features in each eye area are captured at the same time through a hierarchical decoupling attention mechanism guide model, and subtle changes between different eye areas are simulated, so that refined strabismus diagnosis is realized.

The present disclosure relates to a visual perception learning-based apparatus and method for providing stereovision training, the apparatus including: a display module; a memory storing at least one stereovision training-based process for improving strabismus; and a processor that generates first stimulus plate for orthophoria among the both eyes of a trainee and a second stimulus plate for strabismus among the both eyes, and provides the stereovision training by adjusting of a difficulty level of a first stimulus among a plurality of stimuli included in each of the first stimulus plate and the second stimulus plate, wherein the difficulty level can be adjusted through at least one of a three-dimensional effect setting of the stimulus, a shape setting of the stimulus, an interval setting of the stimulus, an edge setting of the stimulus, and a background color setting of the stimulus.

The utility model relates to the technical field of ophthalmology examination instruments, and provides a strabismus measuring instrument which comprises a shell, a measuring window and a camera, the measuring window is embedded in the outer surface of the shell and comprises an electrochromic unit and a control unit, and the electrochromic unit is connected with the camera. The electrochromic unit comprises a shielding area which selectively shields one or two eyes of an observer in a power-on state, and the control unit is used for controlling the shielding area to shield the eyes of the observer; the camera is disposed inside the housing for recording a plurality of images of at least one eye of the observer observing the visual stimulation. According to the scheme, the electrochromic unit is used for shielding light to shield the eye area, the influence of the moving process of the baffle on the watching angle of a patient in the matching process of the servo motor and the baffle is avoided, therefore, the visual traction influence is effectively solved, and due to the fact that the servo motor does not need to be used, the visual effect is improved. And the eye shielding process is quiet and rapid.