One of the great things about studying mathematical tomography is that you discover just how hacked together many modern imaging techniques are. The feeling is very much that there’s a thin margin in which good imaging is possible, and then everything else is based on unfounded assumptions about the usefulness of e.g., Tikhonov regularization and a few numerical experiments.
One of the great things about studying mathematical tomography is that you discover just how hacked together many modern imaging techniques are. The feeling is very much that there’s a thin margin in which good imaging is possible, and then everything else is based on unfounded assumptions about the usefulness of e.g., Tikhonov regularization and a few numerical experiments.