Local principal component based method for detecting activation signals

Abstract

Apparatus for detecting activation signals in functional MRI images comprises MRI apparatus for deriving MRI volume data temporal signals for voxels in image slices, the data being grouped in segments respectively corresponding to active and inactive periods. The apparatus includes apparatus for selecting a core region within each segment, where data within a given core region represents a volume data subset of information within a given segment; for performing principal component analysis for each voxel, utilizing a plurality of volume segment data subsets, active and inactive, so as to result in n-dimensional vectors for each volume segment data subset, each vector containing n elements, where n is the dimension of each segment, and in n eigenvectors, one for each vector; for selecting a number of vectors having highest eigenvalues; for obtaining the inner product for each vector for each volume segment data subset and for number of vectors having highest eigenvalues, resulting in coefficients or projections of a number equal to the predetermined number for each volume segment data subset; for performing the foregoing steps for each voxel; for deriving the mean and standard deviations, utilizing the projections; for deriving an energy measure by taking the square root of the sum of the squares of the temporal signals corresponding to respective segments; for calculating a respective activation term for each voxel; and apparatus for displaying an image wherein respective gray scale values corresponding to the activation terms are assigned to activation terms located in respective coordinate positions.