37 results about "Retinal lesion" patented technology

A method, code and system for planning the treatment a lesion on or adjacent to the retina of an eye of a patient are disclosed. There is first established at least two beam paths along which x-radiation is to be directed at the retinal lesion. Based on the known spectral and intensity characteristics of the beam, a total treatment time for irradiation along each beam paths is determined. From the coordinates of the optic nerve in the aligned eye position, there is determined the extent and duration of eye movement away from the aligned patient-eye position in a direction that moves the patient's optic nerve toward the irradiation beam that will be allowed during treatment, while still maintaining the radiation dose at the patient optic nerve below a predetermined dose level.

A method, code and system for planning the treatment a lesion on or adjacent to the retina of an eye of a patient are disclosed. There is first established at least two beam paths along which x-radiation is to be directed at the retinal lesion. Based on the known spectral and intensity characteristics of the beam, a total treatment time for irradiation along each beam paths is determined. From the coordinates of the optic nerve in the aligned eye position, there is determined the extent and duration of eye movement away from the aligned patient-eye position in a direction that moves the patient's optic nerve toward the irradiation beam that will be allowed during treatment, while still maintaining the radiation dose at the patient optic nerve below a predetermined dose level.

The invention provides an automatic detection method for various retinal focuses in a retinal OCT image. The automatic detection method comprises the following steps: acquiring a retinal 3D OCT image;carrying out detection and preliminary segmentation on the retina 3D OCT image by adopting multiple trained retina focus detection and segmentation models to obtain a focus area subjected to preliminary segmentation; and correcting the preliminarily segmented lesion area to obtain an accurate retinal lesion area. According to the automatic detection method, the retinal focus area in the retinal OCT image can be accurately detected, and various retinal focuses in the retinal OCT image can be quantitatively analyzed, and ideal robustness and accuracy are achieved.

The present invention relates to the use of short interfering nucleic acid molecules (siNA, such as siRNA) that modulate the expression of VEGF-C and/or RhoA involved in neovascular angiogenesis. In the present invention, inhibition of VEGF-C and/or RhoA gene expression results in decreased expression of VEGF-A, which is required for the initiation and persistence of angiogenesis. Furthermore, the present invention also relates to the inhibition of RhoA expression levels and VEGF-C expression levels to gain the benefit of downregulating two different targets required for angiogenesis. The present invention describes compounds, compositions and methods for the inhibition of neovascularization. In certain embodiments, the present invention relates to methods for inhibiting neovascularization, and compounds for treating ocular diseases such as age-related macular degeneration (AMD), diabetic retinopathy, glaucoma, and other neovascular diseases , such as VEGF-C siRNA and RhoAsiRNA.

The invention provides a retinopathy recognition model generation method, a recognition device and equipment. The method comprises the steps: training a preset network model by employing fundus imagesin a training set, obtaining a trained retinopathy recognition model, and enabling the fundus images in the training set to carry classification mark information corresponding to the fundus images, wherein the classification mark information is retina feature classification information corresponding to the eye fundus picture, and the preset network model learns the classification mark informationcontained in the eye fundus picture in the training process. Thus, the trained retinal lesion recognition model can be used for recognizing the retina image contained in the detection picture, and anaccurate classification result of the retinal features is given. According to the method, the device and the equipment provided by the embodiment of the invention, the network model for retinopathy recognition is trained in a deep learning mode, so that the accuracy and the detection efficiency of fundus image recognition are improved.

The present invention relates to methods that involve administration of an anti-S1 P antibody or antibody fragment or derivative to a subject having or suspected of having an ocular disease or condition, including one involving choroidal neovascularization, in order to achieve a desired effect. Such effects include reducing the size of a choroidal neovascularization lesion in the eye, decreasing or resolving retinal pigment epithelial detachment, decreasing central retinal lesion thickness, and preserving or improving visual acuity. Pharmaceutical compositions comprising an anti-S1 P antibody for ocular administration are also provided. The compositions and methods are particularly useful for treating subjects having age-related macular degeneration, particularly exudative or wet age-related macular degeneration.

The invention discloses a premature infant retina plus lesion detection method and system, and the method comprises the steps: firstly inputting a to-be-detected retina posterior pole image into an image quality detection model for quality evaluation, and inputting a qualified image into a blood vessel recognition model to obtain a blood vessel graph; inputting the blood vessel graph into a lesiondetection model, and outputting the probability of the corresponding lesion types of plus, pre-plus and no-plus; and converting the probability of the lesion type of the lesion examination into a corresponding i-ROP lesion score according to a preset score conversion equation to reflect the continuity of the retinopathy degree. According to the invention, the severity of plus lesion is objectively measured, and the severity is tracked over time to provide objective assessment of disease progression or regression; by analyzing the change of the score along with the time, the eyes which progress into plus lesion ROP can be recognized in advance under most conditions for early intervention, disease delay caused by insufficient diagnosis is prevented, the accuracy of lesion degree detection is high, and the ophthalmoscope examination frequency of doctors can be greatly reduced.

The invention discloses a retinopathy detection system based on a lesion attention pyramid convolutional neural network, and relates to a retinopathy detection system. The objective of the invention is to solve the problem of low retinopathy detection accuracy in the prior art. The system comprises an image processing main module used for collecting an original retinopathy image and preprocessing the collected original retinopathy image to obtain a preprocessed original retinopathy image; the neural network main module is used for building a lesion attention pyramid convolutional neural network model; the training main module uses the preprocessed original retinopathy image to train a built lesion attention pyramid convolutional neural network model to obtain a trained lesion attention pyramid convolutional neural network model; and the detection main module is used for loading the trained lesion attention pyramid convolutional neural network model and classifying retinopathy images to be tested. The method is applied to the field of medical image processing.

The invention discloses a retinopathy evaluation model establishing method. The method comprises the steps: enabling a retinopathy evaluation model building system to carry out the image correction ofa plurality of stored retinopathy images, so as to obtain a plurality of corrected images, enabling each retinopathy image to be corresponding to a lesion severity level, and enabling the corrected images to be grouped into a training subset, a verification subset and a test subset, and establishing a retinopathy evaluation model according to each corrected image in the training subset and the corresponding lesion severity level thereof, and each corrected image in the verification subset and the corresponding lesion severity level thereof, and finally detecting the accuracy of the retinopathy evaluation model according to the test subset. In addition, the invention further provides a retinopathy evaluation model establishing system.

The invention discloses agilawood eye-protecting liquid. The agilawood eye-protecting liquid is prepared from the following raw materials in parts by weight: rhizoma corydalis, borneol, borax, medical sodium hyaluronate gel, normal saline and agilawood based on the ratio of 3-8: 20-120: 20-120: 1-3: 800-1300: 20-60. The agilawood eye-protecting liquid can effectively help eye fatigue, dry samples, polyps, lacrimation with wind, cataract, myopia, blurred eyes, dark eye circles and the like; more than 50 compounds in the agilawood have a certain effect of repairing AD diseases; and quercetin, mangiferin, ursolic acid, linalool and linalool in the agilawood have anti-inflammatory and antibacterial effects, especially the quercetin can obviously inhibit BRPC cell apoptosis in a high glucose state, can prevent and treat retinopathy, can inhibit damage of oxidative stress to retinal pigment cells RPE and can protect eyes by preventing cell apoptosis.

The invention discloses a retinal image registration method with affine invariance and a device thereof, and relates to the technical field of image processing. Compared with the whole treatment of the traditional technology, the invention discloses a retinal image registration method with affine invariance. On the basis of a retinal skeletal network image, a local image structure (namely a candidate feature region) is intercepted through two intersections which are communicated with each other in a connected domain; and the local image structure is transformed (rotated, Gaussian filtered andcompressed) into a form suitable for a circular Gaussian filter, so that the problem of visual angle and scale change is solved, the registration precision of multiple images is improved, the construction of complete retinal image information is facilitated, the interference of retinal lesions on diagnosis is reduced, and the diagnosis accuracy is improved.