Corneal topographic map discrimination method and system based on deep learning

A technology of corneal topography and corneal topography, which is applied in the field of medical image processing to achieve high prediction accuracy, avoid misjudgment, and reduce work

Active Publication Date: 2019-11-29
ZHONGSHAN OPHTHALMIC CENT SUN YAT SEN UNIV
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Problems solved by technology

[0005] The present invention provides a method and system for discriminating corneal topography based on deep learning, aiming to solve the problem of lack of corneal morphology discrimination technology for deep learning processing and analysis of corneal topography in the prior art

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  • Corneal topographic map discrimination method and system based on deep learning

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Embodiment Construction

[0018] Such as figure 1 As shown, a method for discriminating corneal topography based on deep learning, including: obtaining the corneal topography to be discriminated and performing image preprocessing to obtain corneal topography feature data; inputting the corneal topography feature data into the corneal topography discrimination model to obtain the corneal topography The corneal morphology output from the discriminant model.

[0019] The invention discloses a method for discriminating corneal topography based on deep learning. The corneal topography obtained in the prior art is preprocessed to obtain corneal topography feature data that can be processed by the corneal topography discrimination model, and the corneal topography feature data is input into the cornea. The topographic map discriminant model is used to obtain the corneal morphology result through the corneal topographic map discriminant model. The corneal topography is analyzed by the corneal topography discr...

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Abstract

The invention discloses a corneal topographic map discrimination method and a corneal topographic map discrimination system based on deep learning. A corneal topographic map obtained in the prior artis preprocessed to obtain corneal topographic feature data capable of being processed by a corneal topographic map discrimination model. The corneal topographic feature data is input into the cornealtopographic map discrimination model, and a corneal morphology result is obtained through the corneal topographic map discrimination model. The corneal topographic map is analyzed through the cornealtopographic map discrimination model to determine the morphological result of the corneal topographic map, a doctor can directly determine the corneal morphology according to the result output by thecorneal topographic map discrimination model, and the prediction accuracy is high. According to the corneal topographic map discrimination method and system based on deep learning provided by the invention, the trained convolutional neural network model is used for carrying out morphological discrimination on the corneal topographic map, and the problem that a corneal morphological discriminationtechnology for carrying out deep learning processing analysis on the corneal topographic map does not exist in the prior art is solved.

Description

technical field [0001] The present invention relates to the technical field of medical image processing, in particular to a method and system for discriminating corneal topography based on deep learning. Background technique [0002] According to the latest research data report of the World Health Organization, the number of myopia patients in China is as many as 600 million, and the poor vision rate of college students aged 19-22 is as high as 80%, and the number of people who are willing to undergo refractive surgery is increasing year by year. All patients who intend to undergo corneal refractive surgery must evaluate the corneal shape by corneal topography before surgery to rule out surgical contraindications. [0003] The current corneal topography is obtained based on modern corneal topography detection technology. The corneal morphology collection system has its corresponding corneal morphology analysis software, which can screen out patients who are not suitable for ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00A61B3/107
CPCG06T7/0012A61B3/107G06T2207/10012G06T2207/20081G06T2207/30041Y02P90/30
Inventor 刘泉谢怡林浩添赵兰琴
Owner ZHONGSHAN OPHTHALMIC CENT SUN YAT SEN UNIV
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