11 results about "Macular disease" patented technology

The invention discloses a myopic maculopathy fundus color photo image classification method and system, and belongs to the technical field of image classification. Obtaining a to-be-analyzed fundus color photo; preprocessing the fundus color photo to extract an effective view area and reduce image acquisition difference interference; and inputting the preprocessed image into a deep learning classification network, and outputting an META-PM classification result corresponding to the myopic maculopathy. According to the method, on the premise of not depending on accurate focus labeling, the global structure and the local focus evidence are fused at the same time, the ordered level relation is explicitly modeled, and the cross-device robustness and the long-tail distribution adaptability are improved.

The present disclosure relates to a pharmaceutical composition for use in preventing or treating retinal or macular diseases, the composition comprising: a polypeptide comprising an amino acid sequence with at least 70% sequence identity with that of TAFA protein (e.g., TAFA1 to TAFA4); a nucleic acid encoding the polypeptide; a vector comprising the nucleic acid, a recombinant virus particle comprising the vector and capsid protein; or a cell comprising the nucleic acid or vector. In addition, the present disclosure relates to an adeno-associated virus (AAV) vector that comprises a nucleic acid encoding a polypeptide having an amino acid sequence with at least 70% sequence identity with that of TAFA protein, and a recombinant virus particle containing the AAV vector and capsid protein. The AAV vector, the recombinant virus, or the composition comprising the same according to the present disclosure can be advantageously used for the prevention or treatment of retinal or macular diseases by recovering damaged retina.

This invention discloses a method and system for grading myopic macular degeneration (ATN) based on multimodal medical imaging. The system includes an image acquisition module for acquiring multimodal retinal images to be graded; a preprocessing module for preprocessing the multimodal images to obtain image sequences that meet preset grading requirements; and a grading module for inputting the image sequences into a pre-stored multimodal multi-task grading model. The model performs feature extraction, multimodal fusion, and multi-task classification on the image sequences, outputting a lesion grade prediction result for each grading task. This invention significantly improves the model's sensitivity to pathological regions by performing pixel-level segmentation of the input images and locating key anatomical structures. In subsequent steps, spatial weighting is applied to CFP image modalities, and specific regions of OCT and OCTA are enhanced, effectively improving the accuracy and robustness of lesion diagnosis and localization.

The invention provides a nucleic acid molecule and application thereof, and belongs to the technical field of biology. Specifically, compared with SEQ ID NO: 1, the nucleic acid molecule has c.1850A > C mutation. The mutation is closely related to myopic maculopathy.

The utility model discloses a light path system and light feeding equipment, and belongs to the technical field of optics. The light path system comprises a light source used for outputting red light; the light feeding element is arranged on an output light path of the light source and used for receiving the red light; the light feeding element comprises a first diffractive optical element and a second diffractive optical element arranged around the first diffractive optical element; wherein the second diffractive optical element is used for deflecting the direction of the red light so as to project the red light to the pupil of the user, and the first diffractive optical element is used for deflecting the direction of the red light so as to project the red light deviating from the pupil of the user. The damage to the macular in the red light treatment process by using the feeding light equipment for a long time is avoided, and the macular degeneration is effectively prevented.

The invention relates to the related technical field of intervention devices, in particular to a non-intrusive intervention device based on 9.34 mu m far infrared light and a use method, the non-intrusive intervention device comprises a pair of tocopherical wave resonance glasses, and a passive tocopherical wave resonance chip is arranged on the tocopherical wave resonance glasses; the passive type birth wave resonance chip comprises a receiving and transmitting module, a processor module and an oscillation module, the receiving and transmitting module is used for receiving bioelectricity and transmitting birth waves, the processor module converts the bioelectricity into a birth wave spectrum wave band, and the oscillation module oscillates and amplifies the processed birth waves; according to the present invention, the problems that the existing PBM cannot efficiently activate the mitochondrial metabolism and lacks the targeting regulation on the fundus macular degeneration core mechanism (such as oxidative stress) are solved, the fundus macular degeneration progress is efficiently and safely inhibited, especially the oxidative stress and the mitochondrial dysfunction of the dry fundus macular degeneration are provided, and the invasive risk is avoided.

The invention provides a maculopathy image recognition method, system and device and a storage medium, and belongs to the field of medical image processing, and the method comprises the steps: obtaining an ophthalmology OCT medical image; the method comprises the following steps: on the basis of a Byol dual-network architecture, updating parameters of a target network in the Byol dual-network architecture through an adaptive moving average (ARMA) method to obtain a pre-trained contrast learning network; and inputting the ophthalmology OCT medical image into the pre-trained contrast learning network, and labeling the OCT medical image with the disease. A CSPDarkNet53 structure is used as a main network, a ResBlock-body module in the CSPDarkNet53 structure is replaced by a PCRBlock residual error network module, PSAM attention is introduced into the PCRBlock residual error network module, and a medical image classification network is obtained; and inputting the screened OCT medical image into a medical image classification network to obtain a maculopathy classification recognition result. And under the condition that the existing data volume is not increased, the classification accuracy of the model on different maculopathy types is improved.

The invention discloses a medical record structuring and standardization generation method for intelligent analysis of macular diseases. The method comprises the following steps: acquiring medical report data and a corresponding macular disease OCT (Optical Coherence Tomography) image; performing manual annotation on the medical report data; segmenting and marking the macular disease OCT image; using the marked medical report data to train a MedBERT model; finely adjusting the SAM model by using the segmented and labeled macular disease OCT image; unstructured macular disease OCT image matching texts are collected, and an extended corpus is constructed; using the trained MedBERT model to extract a structured label of the matched text of the macular disease OCT image; according to the trained MedBERT model and the SAM model after fine tuning, an SAMBERT model is constructed; inputting the macular disease OCT image and the structured label into the SAMBERT model, and performing multi-modal alignment training to generate an image label pair; and generating a standardized medical record text according to the image tag pair.

The present invention relates to constructs and AAV particles comprising wild-type or codon-optimized NDP nucleic acid sequences. The present invention further relates to products and methods for treating one or more of Norrie's disease, age-related hearing loss, diabetic maculopathy and retinopathy, retinal neovascularization, retinal exudation, retinopathy of prematurity (ROP), familial exudative vitreoretinopathy (FEVR), Coats' disease, and other NDP-associated diseases, or other beta-catenin signaling-associated retinal diseases.

1. The name of the design product: fundus examination instrument (ultra-wide-angle all-in-one machine). 2. The use of the design product: a device for fundus examination, which assists medical personnel in screening, diagnosing and monitoring fundus diseases, mainly for the detection and analysis of diabetic retinopathy, retinal detachment and macular degeneration and other fundus diseases. 3. The design points of the design product: the combination of shape and pattern. 4. The picture or photo that best indicates the design points: perspective view 1.

The embodiment of the present application provides a maculopathy edema feature acquisition method in a retinal image and an electronic device, and relates to the technical field of image recognition. The maculopathy edema feature acquisition method in a retinal image comprises the following steps: acquiring a current retinal image to be recognized in a plurality of retinal images; determining an edema brightness threshold of the current retinal image based on the brightness value of the pixels in the vitreous body region of the current retinal image; and determining an edema region in the current retinal image based on the brightness value of each pixel in the current retinal image and the edema brightness threshold of the current retinal image, wherein the brightness value of the pixels in the edema region is less than the edema brightness threshold. The present application can extract the macular edema region in the image based on the brightness value of the pixels in the retinal image.