An intelligent screening system suitable for high myopia complicated by open-angle glaucoma and its establishment method
A technology for open-angle glaucoma and high myopia, which is applied in the field of medical artificial intelligence, can solve problems such as the intelligent screening system for open-angle glaucoma without accurate and efficient high myopia, achieve the effect of reducing visual damage and improving the efficiency of diagnosis and treatment
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Embodiment 1
[0044] Example 1 The present invention is applicable to the establishment process of an intelligent screening system for high myopia complicated with open-angle glaucoma
[0045] The invention is suitable for the establishment process of the intelligent screening system for high myopia complicated with open angle glaucoma as follows: figure 1 shown, as follows:
[0046] 1. Build a deep learning model of an intelligent screening system, which consists of two networks: evaluation and screening. The evaluation network includes a glaucoma OCT deep learning model, a visual field deep learning model, and a fundus photography deep learning model, which can quantitatively evaluate the optic disc shape (rim area, cup volume, cup-to-disc ratio, horizontal cup-to-disc ratio, and vertical cup-to-disc ratio) according to glaucoma OCT. and the thickness of the retinal nerve fiber layer in each quadrant, the thickness of the macular ganglion cell complex, visual field examination to assess ...
Embodiment 2
[0049] Embodiment 2 The intelligent screening system of the present invention suitable for high myopia complicated with open angle glaucoma
[0050] See Figure 4 , Figure 4 It is a structural block diagram of an intelligent screening system suitable for high myopia complicated with open-angle glaucoma according to the present invention. The intelligent screening system suitable for high myopia and open-angle glaucoma includes a storage device 1 , an evaluation module 2 , a screening module 3 and a test evaluation adjustment module 4 .
[0051] Storage device 1: used to store training set information, including the patient's basic information, spherical lens power, intraocular pressure, corneal thickness, A-ultrasound (axial length), glaucoma OCT, visual field, and fundus photography.
[0052] Evaluation module 2: including glaucoma OCT deep learning model, visual field deep learning model, fundus photography deep learning model, used to quantitatively evaluate optic disc s...
Embodiment 3
[0058] Patient Zhang, male, 45 years old, with high myopia in both eyes, went to a local community hospital for glaucoma screening. Doctors check binocular optometry, corneal thickness, A-ultrasound, intraocular pressure, glaucoma OCT, visual field, and fundus photography. The corneal thickness of the right eye was 535.12μm, the axial length was 27.42mm, the intraocular pressure was 17.3mmHg, and the spherical power was -9.00DS. The corneal thickness of the left eye was 536.62 μm, the axial length was 27.72 mm, the intraocular pressure was 16.0 mmHg, and the spherical power was -9.50 DS. The doctor enters the patient information and clinical data into the intelligent screening system of the present invention suitable for high myopia complicated with open-angle glaucoma. The system evaluation results are: right eye: retinal nerve fiber layer thickness (upper quadrant 108.72, lower quadrant 100.82, nasal side 85.25 , temporal side 92.36), normal optic disc shape, macular gangli...
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