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Deep learning-based ophthalmic parameter measuring method and system and equipment

A technology of parameter measurement and deep learning, applied in the field of medical image processing, can solve problems such as no explanation or report found, no data collected, etc., and achieve the effect of automatic identification and positioning

Active Publication Date: 2020-11-17
SHANGHAI JIAO TONG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0008] At present, there is no description or report of similar technology to the present invention, and no similar information has been collected at home and abroad

Method used

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  • Deep learning-based ophthalmic parameter measuring method and system and equipment
  • Deep learning-based ophthalmic parameter measuring method and system and equipment
  • Deep learning-based ophthalmic parameter measuring method and system and equipment

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Embodiment Construction

[0065] The following is a detailed description of the embodiments of the present invention: this embodiment is implemented on the premise of the technical solution of the present invention, and provides detailed implementation methods and specific operation processes. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention, and these all belong to the protection scope of the present invention.

[0066] An embodiment of the present invention provides a method for measuring ophthalmic parameters based on deep learning. The method uses deep learning technology and image processing algorithms to process human eye images, and then identify different parts of the human eye and complete the measurement of ophthalmic parameters. . Such as Figure 5 As shown, the method includes the following steps:

[0067] Step 1: Collect high-definition photos of the patient's face, and automatical...

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Abstract

The invention provides a deep learning-based human eye parameter measuring method and system. The method comprises the steps: acquiring a human face picture, and extracting a left and right eye imagein the picture; identifying different positions in the left and right eye image by employing a deep neural network, including positions of cornea, scleras and inner and outer canthi; and calculating multiple eye parameters at different positions in the left and right eye image. Meanwhile, equipment realized based on the human eye parameter measuring method and system is provided. The deep learning-based human eye parameter measuring method and system and the equipment provided by the invention can realize automatic recognition and positioning of different parts of human eyes; automatic measurement of eye parameters that an ophthalmologist often needs to measure is realized; and the parameter assistance and support are provided for the ophthalmologist to realize analysis of eye disease conditions.

Description

technical field [0001] The present invention relates to a medical image processing technology in the technical field of artificial intelligence, in particular to a method, system and equipment for measuring ophthalmic parameters based on deep learning. Background technique [0002] At present, my country is facing an imbalance between supply and demand of high-quality medical resources, long training period for doctors, high rate of misdiagnosis, rapid changes in disease spectrum, rapid technological changes, aging population, and growth of chronic diseases. As people pay more attention to health, a large demand has led to the rapid development of medical AI. [0003] So far, AI has made great progress in more subdivisions of my country's medical field. For example, in October 2016, Baidu released "Baidu Medical Brain" to benchmark against similar products of Google and IBM. The specific application of Baidu Medical Brain in the medical field, it collects and analyzes a lar...

Claims

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Application Information

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IPC IPC(8): A61B3/10A61B3/107A61B3/11G06K9/00G06N3/04G06N3/08
CPCA61B3/1005A61B3/112A61B3/107G06N3/08G06V40/161G06V40/172G06V40/171G06N3/045
Inventor 翟广涛杨小康朱文瀚朱向阳
Owner SHANGHAI JIAO TONG UNIV
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