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Abstract #2692

Separation of Signal and Noise in Dynamic MRI Data Using the Kolmogorov-Smirnov Test

David S. Smith1, Stephanie Barnes1, Thomas E. Yankeelov1

1Vanderbilt University, Nashville, TN, United States

We present preliminary efforts that indicate that the Kolmogorov-Smirnov statistical test may be an extremely useful method for automatically separating signal from noise in dynamic imaging data, especially when aliased power should be captured but noise should be ignored. We compare to Otsu's method and demonstrate an improved automatic classification of signal and noise in in vivo tumor-bearing mouse data.