Dynamic scale distribution-based retinal vessel extraction method and system

A retinal blood vessel and extraction method technology, applied in the field of retinal blood vessel extraction and system based on dynamic scale allocation, can solve problems such as wrongly segmented pixels, difficult to segment blood vessels, etc.

Active Publication Date: 2017-02-15
SHANDONG UNIV
View PDF2 Cites 29 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method still has certain limitations: it uses three filters of different scales to extract retinal blood vessels. For the blood vessel widths that vary greatly, there are still some blood ve

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
  • Dynamic scale distribution-based retinal vessel extraction method and system
  • Dynamic scale distribution-based retinal vessel extraction method and system
  • Dynamic scale distribution-based retinal vessel extraction method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0140] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0141] Such as figure 1 As shown, the retinal blood vessel extraction method based on dynamic scale allocation includes the following steps:

[0142] Step (1): Image preprocessing

[0143] Further, the steps of the step (1) are:

[0144] Step (1-1): Extract the green channel component of the color image: the original color retinal image contains three channels of red, green and blue, and only select the green channel with high contrast and low noise as the initial processing object;

[0145] Step (1-2): Multi-scale top-hat transformation: use circular structural elements with unchanged shape and increased size to perform multi-scale top-hat transformation on the initial processing object to enhance the contrast of the initial processing object;

[0146] Step (1-3): Linear stretching of the histogram based on Gaussian curve fitting: Perform linear str...

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

The present invention discloses a dynamic scale distribution-based retinal vessel extraction method and system. The method includes the following steps of: retinal image preprocessing: contrast enhancement is performed on the green channel component of a color retinal image; image segmentation: the preprocessed retinal image is segmented into a set number of sub-images; vessel classification: the vessels of each sub-image are divided into three categories, namely, a large category, a medium category and a small category; dynamic scale allocation: filters of different scales are dynamically selected to enhance vessels of different widths; multi-scale matched filtering; threshold processing: vascular structures are extracted, nonvascular structure was removed, the extraction results of all the sub-images are re-spliced, so that a retinal vessel network binary image can be obtained; and post-processing: post-processing is carried out, so that a high-segmentation accuracy retinal vessel network image can be obtained. With the method and system of the invention adopted, the vessel extraction of the retinal image can be realized; excessive estimation of the widths of the vessels can be avoided when complex nonvascular structures are removed; and simpler and more accurate retinal vessel extraction can be realized.

Description

technical field [0001] The invention relates to a method and system for extracting retinal blood vessels based on dynamic scale allocation. Background technique [0002] So far, the commonly used retinal vessel automatic extraction algorithms are: [0003] 1. Algorithm based on retinal blood vessel tracking method. This type of method can extract the retinal blood vessel network relatively completely, but the complexity of the algorithm is high and the amount of calculation is large. In addition, for some retinal blood vessel images with low contrast, the extraction accuracy of such algorithms is not enough. Among them, the typical retinal blood vessel tracking algorithm is based on the fuzzy C-means clustering algorithm proposed by Tolias in 1998, which selects a suitable seed point at the beginning of the blood vessel (optic disc), and thus performs the whole retinal blood vessel network. track. Establish a one-dimensional model of the retinal blood vessel cross-sectio...

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): G06K9/00G06K9/36G06K9/34G06K9/40G06K9/44G06T5/00G06T3/40
CPCG06T3/4038G06T5/007G06T2207/30101G06T2207/30041G06V40/19G06V40/193G06V40/197G06V40/10G06V40/14G06V10/20G06V10/30G06V10/34G06V10/267G06F18/24
Inventor 魏莹勾多多闫莉莉
Owner SHANDONG UNIV
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