Abstract #3604

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

Bo Zhu^1,2,3, Neha Koonjoo^1,2,3, Bragi Sveinsson^1,2,3, and Matthew S Rosen^1,2,3

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.

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

Join Here