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

Method for detecting brain function communicated area based on signal sparse approximation

A technology of connected areas and detection methods, applied in the directions of diagnostic recording/measurement, medical science, sensors, etc., can solve problems such as limited functional connected area detection

Inactive Publication Date: 2015-02-11
SHANGHAI MARITIME UNIVERSITY
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, although the current data processing and analysis methods can complete the detection of functional areas to a certain extent, they all have many deficiencies and defects, and the accuracy of functional area positioning needs to be further improved
For example, the fuzzy clustering analysis method is limited by the iteration speed, fuzzy index, and the number of estimated functional areas; independent component analysis is completely subject to the independent assumption of strong functional area source signals, which limits the detection of functionally connected areas

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
  • Method for detecting brain function communicated area based on signal sparse approximation
  • Method for detecting brain function communicated area based on signal sparse approximation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0013] Specific embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0014] Such as figure 1 and combine figure 2 As shown, the present invention discloses a method for detecting brain functional connected regions based on signal sparse approximation, the method comprising the following steps:

[0015] Step 1, wavelet packet decomposition: for each time point data of the functional magnetic resonance data, respectively carry out 3 layers of one-dimensional wavelet packet decomposition, wherein the selection of the wavelet base, in the present invention, the wavelet system has anti-symmetry and positive The db2 wavelet base in the Daubechies (abbreviated as: db) family with intersecting and biorthogonal properties; after decomposing the wavelet packet, the corresponding wavelet tree (such as figure 2 shown), each node in the wavelet tree has different sparse attributes. , and an efficient sparse approximation...

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 method for detecting a brain function communicated area based on signal sparse approximation. The method comprises the following steps: 1, performing wavelet packet decomposition on each time point data in a functional magnetic resonance signal to obtain a wavelet tree on original time point data; 2, carrying out sparsity measurement on nodes in the wavelet tree, and selecting the node with strongest sparsity in the wavelet tree to form an effective sparse approximation data set on original functional magnetic resonance data; and 3, carrying out hybrid matrix optimization on the formed sparse approximation data set by adopting independent content analysis, and reconstructing a source signal in a functional area in combination with an original functional magnetic resonance mixed signal to finish accurate positioning and detection of the functional area. According to the method, sparse approximation of original mixed data is obtained by utilizing the more general supposed sparsity of the functional magnetic resonance signal, and the source signal is separated through the independent content analysis and the signal reconstruction, so that the purpose of accurately positioning the brain function communicated area is achieved.

Description

technical field [0001] The invention relates to a method for detecting functionally connected areas of the human brain based on functional magnetic resonance imaging technology, in particular to a method for accurately locating and detecting functionally connected areas of the human brain based on a blind source signal separation method based on functional magnetic resonance mixed signal sparse approximation . Background technique [0002] Functional magnetic resonance imaging technology is a new type of magnetic resonance imaging technology that began to emerge in the 1990s. This technology combines the information of function, anatomy and imaging, and provides strong technical support for traditional magnetic resonance technology from single morphological structure research to system research combined with function. Cognitive research, diagnosis of brain diseases and mental diseases, etc. provide favorable technical support. In the study of functionally connected areas o...

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 Patents(China)
IPC IPC(8): A61B5/055
Inventor 王倪传曾卫明王晗姚胜南
Owner SHANGHAI MARITIME UNIVERSITY
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