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376 – Contributed Oral Poster Presentations: Section on Statistical Computing
Separation of Several Aliased Images to Increase Volume Speed
Daniel Rowe
Marquette University
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. Over the last decade, techniques have been developed to sample less data within an image thus decreasing the acquisition time for an image of each slice. However, a new thrust is to simultaneously excite multiple slices that make up a volume and sample 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 technique and statistical description has been presented for aliasing and separating two complex-valued slices with a single coil image. The thrust of this work is to extend that work to separate complex-valued images for a higher numbers of aliased slices and present statistical implications.