Justin P. Haldar1, Joong H. Kim2, Sheng-Kwei Song2, Zhi-Pei Liang1
1Electrical & Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States; 2Radiology, Washington University in St. Louis, St. Louis, MO, United States
Diffusion imaging experiments have previously been demonstrated to accurately quantify spinal cord white matter injury and disease in various rodent models. One limitation of these experiments is that substantial signal averaging has been necessary to achieve sufficient signal-to-noise ratio (SNR). Averaging necessitates long imaging experiments, which can be stressful for imaging subjects and limits throughput. In this work, we demonstrate that an appropriate statistical denoising strategy can be used in place of averaging, leading to experiments that are 4 times faster but are still capable of quantifying spinal cord disease and injury in mouse models of multiple sclerosis and trauma.