GDL-FIRE4D: Deep Learning-based fast 4D CT image registration
Related Research units
Abstract
time is reduced to a few seconds (here: 60-fold speed-up); and (3) dropout-based uncertainty maps do not correlate to across-DIR vector field differences, raising doubts about applicability in the given context.
Bibliographical data
Original language | English |
---|---|
Title of host publication | Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 |
Editors | Alejandro F. Frangi, Julia A. Schnabel, Christos Davatzikos, Carlos Alberola-López, Gabor Fichtinger |
REQUIRED books only: Number of pages | 9 |
Volume | 11070 |
Publisher | Springer |
Publication date | 09.2018 |
Edition | 1 |
Pages | 765 - 773 |
Publication status | Published - 09.2018 |