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Abstract #3130

Objective Assessment of T2-Based Liver Lesion Classifiers

Christian Graff1, Eric W. Clarkson2, Maria I. Altbach2

1Division of Imaging and Applied Math/OSEL/CDRH, U. S. Food and Drug Administration, Silver Spring, MD, United States; 2Department of Radiology, University of Arizona, Tucson, AZ, United States

Classification of lesions as benign or malignant is an important imaging task. In liver, transverse relaxation time (T2) can be used as a classifier. Recently a radial fast spin-echo technique has been developed to obtain T2 estimates within a single breath-hold during which under-sampled radial k-space lines are acquired. The degree of under-sampling in this technique motivated the development of various post-processing techniques that attempt to enforce prior information to compensate for data under-sampling. In this work we evaluate these proposed algorithms through the use of a receiver-operating-characteristic (ROC) based metric which directly measures the classification performance of each algorithm.