Brain activation region detection method based on correlation analysis

Abstract

The present invention provides a brain activation region detection method based on correlation analysis. The method comprises the following steps: Step 1: calculating correlation coefficients between the time series of each voxel and the time series of the neighborhood voxel; Step 2: solving the average of all the correlation coefficients and obtaining a correlation parameter of each voxel; and Step 3: sorting correlation parameters of all voxels, setting a threshold value, comparing correlation parameter of each voxel with the threshold value, and according to the comparison result, dividing each voxel to the activation or inactivation region. According to the method provided by the present invention, a lot of calculation work is saved, the purpose can be reached only through calculating the correlation parameter of each voxel and selecting the voxel with a larger correlation parameter; and the activation region can be obviously detected, the same detection effect can be reached by the method provided by the present invention as the former complicated calculation method, and the method is easy to operate and can save a lot of detection time.

Description

technical field [0001] The invention belongs to the field of fMRI data analysis, in particular to a method for detecting brain activation regions based on correlation analysis. Background technique [0002] Functional Magnetic Resonance (fMRI, functional Magnetic Resonance Imaging) is a technical means to detect neural activity signals in the human brain. Its basic principle is that under a certain magnetic field strength, the hydrogen atoms in the human body will resonate with a certain frequency of radio frequency pulses to absorb energy, and will release the absorbed energy after a period of time. Because different human body structures release energy at different times, the intensity of energy released at the same time is also different. According to this difference, different brain tissue structures can be separated. When the brain nerves are active, it will cause changes in the blood oxygen level in the blood vessels around the brain nerves. Variations in blood oxyge...

AI Technical Summary

Problems solved by technology

The current relatively simple method, such as Time Cluster Analysis (TCA, Time Clustering Analysis), its principle is to find the maximum point of the time series of each voxel of the brain, and then define a point in the time series that has a maximum value. The number of voxels of the value is the time cluster, and the time point when the time cluster is greater than a certain threshold is considered to be the time point of brain activation, and the area where these voxels that make up the time cluster are located is the activation area, although this method is simple from the calculation point of view Some, but the detection effect is not satisfactory

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