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An intelligent prediction system for the prognosis of high myopia cataract surgery

A technology for high myopia and cataract, applied in the field of medical artificial intelligence, can solve the problems of high myopia cataract surgery prognosis intelligent prediction system has not been reported, to avoid the waste of medical resources and economic losses, reduce the gap, improve the accuracy of prediction Effect

Active Publication Date: 2021-12-10
EYE & ENT HOSPITAL SHANGHAI MEDICAL SCHOOL FUDAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] But about a kind of high myopia cataract operation prognosis intelligent prediction system of the present invention, there is no report yet

Method used

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  • An intelligent prediction system for the prognosis of high myopia cataract surgery
  • An intelligent prediction system for the prognosis of high myopia cataract surgery
  • An intelligent prediction system for the prognosis of high myopia cataract surgery

Examples

Experimental program
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Effect test

Embodiment 1

[0035] Please refer to the attached Figure 4 , attached Figure 4 It is a structural block diagram of an intelligent prediction system for high myopia cataract surgery prognosis of the present invention. The high myopia cataract operation prognosis intelligent prediction system includes a storage device 1 , an evaluation module 2 , an examination module 3 and a test evaluation adjustment module 4 .

[0036] Storage device 1: used to store the information in the training set, including basic information of the patient, preoperative best corrected visual acuity, axial length, corneal astigmatism, anterior segment photos, fundus photos, fundus OCT and postoperative best corrected visual acuity;

[0037] Evaluation module 2: According to the degree of lens opacity in the anterior segment image, make LOCSIII classification, build a deep learning model for the degree of lens opacity, and evaluate the degree of fundus lesions according to the results of fundus photography and OCT; ...

Embodiment 2

[0046] Construct the deep learning model of the intelligent prediction system, which is composed of two networks: evaluation and prediction; the evaluation network makes LOCSIII classification according to the degree of lens opacity in the anterior segment image, and builds a deep learning model for the degree of lens opacity. Evaluate the degree of fundus lesions and build a fundus evaluation model; the deep learning model of lens turbidity is a hierarchical regression algorithm based on convolutional neural network (CNN). The deep learning framework adopted is based on VGG, Inception, ResNet, etc. Since postoperative visual acuity prediction is closely related to the degree of fundus lesions, the system features image enhancement algorithms in the fundus evaluation model to reduce the impact of refractive media turbidity on image quality, and identify and grade all fundus lesions as much as possible. At the same time, according to the fundus photo and the corresponding image ...

Embodiment 3

[0051] The female patient, 46 years old, had blurred vision in the right eye for 1 year. She was treated in our hospital and denied diabetes, hypertension, other eye diseases or surgery history. Ophthalmological examination showed that the best corrected visual acuity of the right eye was 0.4, the axial length of the eye was 27.1mm, and the corneal astigmatism was -0.58D. The doctor entered the patient information and clinical data into the high myopia cataract surgery prognosis intelligent prediction system, and the system evaluation result was: high myopia cataract in the right eye (LOCSIII grade N3, no obvious abnormality in the fundus), and the estimated postoperative best corrected visual acuity range was 0.8 -1.0. The patient agreed to the operation, and the best corrected visual acuity of the right eye was 1.0 one day after the operation, and the patient was satisfied.

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Abstract

The invention relates to an intelligent prediction system for the prognosis of highly myopic cataract surgery. The system can evaluate the degree of cataract opacity on the anterior segment photos, evaluate the fundus condition according to the fundus photos and OCT images of the fundus, and then integrate other clinical data of the patient to provide the prediction of the best corrected visual acuity range for high myopia cataract patients after surgery. Its advantages are as follows: through repeated testing and parameter adjustment to achieve a high accuracy rate, solve the most concerned problems of clinicians and patients, help clinicians accurately predict postoperative visual acuity, provide patients with intuitive postoperative result prediction, reduce The gap between patient expectations and results can be improved to improve patient satisfaction.

Description

technical field [0001] The invention relates to the technical field of medical artificial intelligence, in particular to an intelligent prediction system for the prognosis of highly myopic cataract surgery. Background technique [0002] High myopia cataract refers to cataract patients whose axial length is greater than or equal to 26mm. Such patients usually have myopia exceeding -6.0D or even -30.0D before surgery, and high myopia is not only a change in diopter, but may be combined with a series of pathological changes , including leopard-like fundus, posterior staphyloma, lacquer cracks, peri-optic disc atrophy, chorioretinal atrophy, choroidal neovascularization, retinoschisis, and macular hole. For cataract patients and surgeons, postoperative visual acuity and visual quality are the most important concerns. However, due to the complexity of fundus lesions in patients with high myopia and the opacity of the refractive medium caused by cataract, the details of fundus les...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B3/18A61B5/00
CPCA61B3/185A61B5/4848
Inventor 竺向佳何雯雯卢奕丁大勇
Owner EYE & ENT HOSPITAL SHANGHAI MEDICAL SCHOOL FUDAN UNIV
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