MDP-net-based vitreous opacity grading screening method and device

A vitreous opacity, mdp-net technology, applied in the field of image processing and deep learning, can solve the problems of low accuracy, doctors can only make intuitive judgments, consume doctors' energy, etc., and achieve fast results.

Pending Publication Date: 2022-03-04
FOSHAN UNIVERSITY
View PDF0 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method has the problems of strong dependence on doctors' clinical experience and low diagnostic efficiency, and it is difficult to obtain accurate and reliable screening resu

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • MDP-net-based vitreous opacity grading screening method and device
  • MDP-net-based vitreous opacity grading screening method and device
  • MDP-net-based vitreous opacity grading screening method and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] The preferred embodiments of the present invention will be described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described here are only used to illustrate and explain the present invention, and are not intended to limit the present invention.

[0028] refer to Figure 1a , Figure 1b and Figure 1c , MDP-net network construction includes:

[0029] Encoding part (downsampling)

[0030] 1. First run the software python and the input image size is 256*256;

[0031] 2. For the first time, it is input to a standard convolution layer with a number of convolution kernels of 96 and a kernel size of 3*3;

[0032] 3. After that, 5 Denseblock operations were used. The Denseblock block is composed of multiple convolutional layers and Concatenate cascade layers. The specific structure is shown in the figure.

[0033] 4. Also took a total of 5 downsampling operations, interspersed between each block using LeakyRelu ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

According to the MDP-net-based vitreous opacity grading screening method and device, a crystalline lens, a quasi-trapezoidal vitreous cavity and a turbid focus area in an eye vitreous ultrasonic image can be segmented through deep learning by an eye vitreous ultrasonic image adaptive segmentation model and a severity classification algorithm; according to the method, the vitreous opacity severity of the patient can be quickly and accurately judged and screened after image training by applying the deep learning technology, and the obtained result is quick, objective, accurate and stable.

Description

technical field [0001] The present invention relates to image processing and deep learning technology, in particular to a vitreous opacity grading screening method and device based on MDP-net (full name: Multi-output Dense Pyramid network, named Multi-output Dense Pyramid Network). Background technique [0002] The specific condition of vitreous opacity can be reflected by the shape and size of opacity foci in the vitreous cavity in the images taken by ophthalmic B-ultrasound equipment, but the existing instruments fail to provide the quantitative indicators required for the diagnosis of vitreous opacity. The known grading method for the severity of vitreous opacity is: doctors evaluate and analyze vitreous B-ultrasound images based on clinical experience and professional knowledge. This method has the problems of strong dependence on doctors' clinical experience and low diagnostic efficiency, and it is difficult to obtain accurate and reliable screening results in a short t...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06T7/00G06T7/11G06T7/136G06T7/155
CPCG06T7/0012G06T7/11G06T7/136G06T7/155G06T2207/20016G06T2207/30041
Inventor 刘明迪覃楚渝杜倩宜陈子源杨凌风劳俊星郭学东王陆权熊红莲曾亚光韩定安
Owner FOSHAN UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap