Nicole Seiberlich1, Hyun J. Jeong2,
Timothy J. Carroll2, Mark A. Griswold1,3
1Radiology, Case Western Reserve
University, Cleveland, OH, United States; 2Radiology, Northwestern
University, Chicago, IL, United States; 3Biomedical Engineering,
Case Western Reserve University, Cleveland, OH, United States
Gradient
Descent with Sparsification, a novel image reconstruction technique, has been
applied to the generation of images from highly undersampled MR Angiography
data. Unlike other techniques, this method can be implemented using no
external para-meters, allowing completely unsupervised reconstructions. The
extremely high acceleration factors shown here are made possible by
initializing a given time frame with the previous frame, such that only
differences must be reconstructed. Temporal resolutions of 180ms/frame have
been achieved by undersampling the collected data by a factor of R~75 (using
4 projections per partition per frame) with no venous contamination and
little residual streaking or blurring.