no code implementations • 6 Sep 2021 • Monika Grewal, Jan Wiersma, Henrike Westerveld, Peter A. N. Bosman, Tanja Alderliesten
Conclusions: DCNN-Match learns to predict landmark correspondences in 3D medical images in a self-supervised manner, which can improve DIR performance.
2 code implementations • 21 Jan 2020 • Monika Grewal, Timo M. Deist, Jan Wiersma, Peter A. N. Bosman, Tanja Alderliesten
We tested the approach on 22, 206 pairs of 2D slices with varying levels of intensity, affine, and elastic transformations.