Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Medical image cutting method based on oscillatory network

A technology of oscillating networks and medical images, applied in image enhancement, image data processing, biological models, etc., can solve problems such as position deviation, unreasonable contours, and missing contours

Inactive Publication Date: 2008-01-09
HANGZHOU DIANZI UNIV
View PDF0 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

If the detection accuracy is improved, the false edges generated by noise will lead to unreasonable contours; if the noise immunity is improved, contour missed detection and position deviation will occur

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 cutting method based on oscillatory network
  • Medical image cutting method based on oscillatory network
  • Medical image cutting method based on oscillatory network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0035] The core idea of ​​the present invention is to establish an oscillating network similar to the oscillating activity of neurons in the visual cortex to visual features, and apply it to medical image segmentation to better distinguish "target" and "background", and in Under the premise of satisfying the segmentation accuracy, the time complexity and space complexity are greatly reduced, and it has important practical promotion value.

[0036] The medical image segmentation method based on the oscillation network of the present invention will be described in detail below in conjunction with the accompanying drawings

[0037] The method of the invention mainly includes four steps: (1) establishing an oscillation network. (2) Search in the network to find the oscillation initiation point. (3) Oscillate from the starting point, and iteratively expand to the surrounding neighborhood. (4) After the oscillation is over, the "target" and "background" are segmented based on the ...

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 existed method has problems of: (1) difficult to divide the uneven illuminated picture with a unified threshold; (2) sensitive to the unevenness of noise and gray scale. This invention includes steps of: (1) building a oscillating net; (2) searching the oscillation starting point in the net; (3) starting the oscillation from the starting point and iterative extending to the neighbor domain; (4) after oscillation, distinguishing ' target' from 'background' depending on if possessing a mark. In picture dividing methods, This method combines the advantages of both the margin tracing method and the domain generating method (DG). It obtains the same result as DG, but greatly reduces the time / space complexity and greatly raises the toughness and the dividing speed. It will have an extensive develop foreground in practical application.

Description

technical field [0001] The invention belongs to the technical field of image information processing, and relates to a medical image segmentation method, in particular to an image segmentation method based on an oscillation network. Background technique [0002] Image segmentation is a basic problem in computer image processing and the first step in many subsequent image analysis tasks, especially for image recognition and description, image visualization and object-based image compression are highly dependent on the segmentation results. Image segmentation is a key step from image processing to image analysis, and it is also a basic computer vision technology, because image segmentation, target separation, feature extraction and parameter measurement transform the original image into a more abstract, more The compact form makes higher-level analysis and understanding possible. [0003] In general, segmentation problems consist of segmenting similar blocks in a given image i...

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): G06T5/00G06N3/00
Inventor 李轶范影乐
Owner HANGZHOU DIANZI UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com