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Abstract #2619

Lower Extremities Perfusion Imaging with Low-Rank Matrix Completion Reconstruction

Jieying Luo1, Taehoon Shin1, Tao Zhang1, Bob S. Hu2, Dwight G. Nishimura1

1Electrical Engineering, Stanford University, Stanford, CA, United States; 2Palo Alto Medical Foundation, Palo Alto, CA, United States

An accurate measurement of lower extremities perfusion is potentially of significant help in the assessment of peripheral arterial disease. This work investigates and optimizes the use of low-rank matrix completion reconstruction for this application. As verified using both numerical simulations and retrospectively undersampled in-vivo data, reconstruction performance is improved by the use of reference images and a complementary uniformly random undersampling pattern. With this method, volumetric perfusion imaging of the lower extremities with temporal resolution of 2 seconds can be achieved.