1 code implementation • 3 Oct 2023 • Louis D. van Harten, Jaap Stoker, Ivana Išgum
To improve robustness, we propose a deformable registration method using pairs of cycle-consistent Implicit Neural Representations: each implicit representation is linked to a second implicit representation that estimates the opposite transformation, causing each network to act as a regularizer for its paired opposite.
no code implementations • 12 Nov 2019 • Louis D. van Harten, Jelmer M. Wolterink, Joost J. C. Verhoeff, Ivana Išgum
We show that this uncertainty measure can be used for two kinds of online quality control.
no code implementations • 12 Nov 2019 • Louis D. van Harten, Jelmer M. Wolterink, Joost J. C. Verhoeff, Ivana Išgum
We empirically assess how many clinical delineations would be sufficient to train a CNN for the segmentation of OARs and find that increasing the training set size beyond a limited number of images leads to sharply diminishing returns.