Unlock instant, AI-driven research and patent intelligence for your innovation.

Medical image segmentation method based on hybrid active contour model

An active contour model, medical image technology, applied in the field of medical image processing, can solve the problems that the heterogeneous area cannot be processed well, noise and weak edge sensitivity, etc., to achieve good segmentation effect, strong capture ability, strong anti-noise sexual effect

Inactive Publication Date: 2018-06-01
LIAONING NORMAL UNIVERSITY
View PDF4 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The active contour model based on global information can effectively deal with image noise and weak edges, but it usually cannot handle the heterogeneous regions of the image well
Models based on local information can handle the above problems well, but the model is sensitive to noise and weak edges

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
  • Medical image segmentation method based on hybrid active contour model
  • Medical image segmentation method based on hybrid active contour model
  • Medical image segmentation method based on hybrid active contour model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0024] The medical ultrasound image segmentation model based on the combination of global and local area information provided by the examples of the present invention is carried out according to the following steps;

[0025] Step 1: Initialize the level set function and the image to be segmented ,in for the image The pixel coordinate point;

[0026] Step 2: Calculate the weight information of image pixels :

[0027] (1)

[0028] in, , Indicates the positions corresponding to different pixels;

[0029] Step 3: Calculate global information and local information , the corresponding expression is:

[0030] and (2)

[0031] in, is the level set function The Heaviside function;

[0032] Step 4: Calculate the global energy value of the image and local energy values :

[0033] (3)

[0034] Step 5: Using the finite difference method, update the level set function :

[0035] (4)

[0036] in, is the level set function The Dirac functi...

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 invention discloses a medical image segmentation method based on a hybrid active contour model. Image global information and local information are combined. The model is enabled to have high noiseresistance for the image and have high capture capacity for the image edge by the global information. Heterogeneous area segmentation is enabled to be more accurate by the local information. The image global information and the local information are combined so that the image of which the background and the internal structure are complex can be processed. The experiment result proves that the medical image of low contrast and complex structure can be segmented, and the image including noise, weak edges and heterogeneous areas can also acquire great segmentation effect.

Description

technical field [0001] The invention relates to the field of medical image processing, in particular to a medical image segmentation method based on a mixed active contour model. Background technique [0002] In clinical medical detection, doctors need to diagnose the disease through the precise location and shape of the lesion in the image. Due to the influence of external factors such as medical imaging equipment, uneven illumination, and ray energy scattering, heterogeneous phenomena such as noise, weak edges, and uneven gray distribution often appear in the process of acquiring medical digital images, which brings great difficulties to image segmentation. a certain degree of difficulty. In recent years, image segmentation methods based on active contour models have been widely used in the processing of medical images, which mainly include: active contour models based on global information and local information. Active contour models based on global information can effe...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/12G06T7/149
CPCG06T7/0012G06T7/12G06T7/149G06T2207/30096
Inventor 方玲玲王相海
Owner LIAONING NORMAL UNIVERSITY
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com