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Abstract #3604

Quantitative characterization of image reconstruction training dataset complexity with Rademacher Complexity measures

Bo Zhu1,2,3, Neha Koonjoo1,2,3, Bragi Sveinsson1,2,3, and Matthew S Rosen1,2,3
1Department of Radiology, A.A Martinos Center for Biomedical Imaging/MGH, Charlestown, MA, United States, 2Harvard Medical School, Boston, MA, United States, 3Department of Physics, Harvard University, Cambridge, MA, United States

Here we propose to quantitatively measure the data complexity of training datasets using the Rademacher Complexity metric, and demonstrate its effectiveness in analyzing dataset composition and its effect on neural network training for image reconstruction tasks.

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