Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Segmentation method and device for MR image

An image and image acquisition technology, which is applied in the field of medical image processing, can solve the problems of poor image segmentation accuracy and achieve the effect of improving the accuracy rate

Active Publication Date: 2015-04-01
SHENZHEN INST OF ADVANCED TECH
View PDF3 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the embodiments of the present invention is to provide a method for segmenting MR images, which aims to solve the problem that the accuracy of image segmentation is not good due to the direct application of algorithms based on sparse representation to image segmentation in the prior art

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
  • Segmentation method and device for MR image
  • Segmentation method and device for MR image
  • Segmentation method and device for MR image

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0020] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0021] figure 1 The implementation process of the MR image segmentation method provided by the embodiment of the present invention is shown, and the details are as follows:

[0022] In S101 , the dictionary learning of each modality is respectively performed through multi-modal sample MR images.

[0023] Before segmenting the test MR image, first use the training samples of the multi-modal training image to train the dictionary of different states in each mode required for image segmentation. The training process of the dictionary is a process of joint sparse optimization. The multi-modal classif...

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 belongs to the field of medical image processing technologies, and provides a segmentation method and device for an MR image. The method includes the steps that dictionary learning in all modes is performed on the multi-mode MR image; a multi-mode joint sparse representation model is established; through the multi-mode joint sparse representation mode, the test MR image is represented as a linear combination of a few atoms under a dictionary in a joint sparse mode, and the sparse representation coefficient of the test MR image is obtained through sparse coding; according to the sparse representation coefficient of the test MR image, all pixels of the test MR image are classified, so that an image segmentation result is obtained. Through the multi-mode joint sparse representation model, multi-variable joint sparse representation can be performed in combination with information provided by the multi-mode MR image, and the accuracy of image segmentation is greatly improved.

Description

technical field [0001] The invention belongs to the technical field of medical image processing, in particular to an MR image segmentation method and device. Background technique [0002] Magnetic resonance (Magnetic Resonance, MR) imaging technology has high soft tissue resolution and non-invasiveness. It can perform tomographic imaging on different anatomical parts. It can achieve image contrast weighting with different parameters to obtain high tissue resolution, high definition and The ability to provide a variety of diagnostic information has been widely used in the field of brain tumor diagnosis. In order to quantitatively analyze the local lesions of brain tumors, it is necessary to segment the tumor in the brain image to determine the volume, size and location of the tumor. [0003] Sparse representation is a newly developed machine learning method. This method learns the training samples, trains the corresponding dictionary of this type of samples, and sparsely rep...

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): G06T7/00
CPCG06T7/0014G06T7/10G06T7/149G06T7/344G06T2207/10088G06T2207/20081G06T2207/30016
Inventor 李玉红秦璟贾富仓王琼王平安
Owner SHENZHEN INST OF ADVANCED TECH
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
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