Statistical Image Reconstruction of Two Simultaneously Excited fMRI Slices
American Statistical Association
Proceedings of the 2012 Joint Statistical Meetings, "Statistics: Growing to Serve a Data-Dependent Society"
In functional MRI, each slice in a volume is traditionally excited individually, measuring enough data in a single k-space array to reconstruct an image for that slice. However, simultaneously exciting multiple slices that make up a volume can produce sufficient data in a single k-space array to represent multiple slices. This single array of k-space data can be reconstructed into a single image representing the aliased slices, and then separated into individual images for each slice. A statistical description of an image representing two aliased slices using a single channel coil is presented. Image separation, utilizing calibration reference scans of each slice, through both an existing magnitudeonly approach and a new complex-valued approach are described, and the statistical properties of these two image separation approaches are presented. Through examining the expected mean image and covariance matrix of the separated images, it is theoretically shown that correlations remain between images of slices through both approaches. Since the image separation process is not the inverse of the image aliasing process, the separated images have different statistical properties than slices excited individually. Through both theoretical and experimental data, the complex-valued approach is shown to out-perform the magnitude-only approach.