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.