Meeting Banner
Abstract #4067

Acceleration of high-resolution proximal femur MRI using compressive sensing and sparsity in a retrospective study

Brian-Tinh Duc Vu1,2, Brandon Jones1,2, Winnie Xu2, Gregory Chang3, and Chamith Rajapakse2,4
1Bioengineering, University of Pennsylvania, Philadelphia, PA, United States, 2Radiology, University of Pennsylvania, Philadelphia, PA, United States, 3Radiology, Center for Biomedical Imaging, New York University, New York, NY, United States, 4Orthopaedic Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States

Retrospective compressive sensing techniques demonstrate promise accelerating acquisition of high-resolution images of the femur while maintaining sufficient image quality to assess fracture risk. While the trabecular bone microstructure was preserved at an undersampling rate of 30%, lower sampling rates of 10% and 5% exhibited visually apparent artifacts and image degradation. Similarly, bone stiffness at 30% resembled fully sampled data but the error increased as sampling rate decreased. Nevertheless, the results show that compressive sensing is a promising candidate for accelerating the acquisition rate, and further prospective studies are needed to further validate this finding.

This abstract and the presentation materials are available to members only; a login is required.

Join Here