Meeting Banner
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.

Abstract PDF

Keywords

accelerated acceleration accurate accurately acquisition added addition agree agreeing alto amplitude arterial assessment audience beginning behavior blocks blurring calibration candidates challenging clinicians coefficient collect combined complementary completion consecutive considered constrained continuation contrast coverage covering curve curves dataset described designed desired disease distribution dividing dynamic dynamics efficiently electrical enables engineering enhanced equals equivalent error even extremities facilitates fact fast fidelity field finally fixed form foundation frame frames fully functions greatly help highly improve improved in vivo index injection matrix medical minx missing moreover muscle needed noise noiseless normalized numerical optimized outer pattern patterns perfusion peripheral physicists pixels portion position problem promising property propose proposed quantitative random rank reconstructed reconstruction reconstructions recovered reduced redundancy regularization represent required reshaping resolution retrospectively rise root sample sampled semi series serve several shin simulated simulation simulations singular slope solved solving space spatial spirals square stack static successfully sufficient target tech temporal trading trajectories trajectory true uniformly unique volumetric yields