4 citations · 20 across the 28 of their papers we have counts for
6 papers · 1 filter
A Tournament of Transformation Models: B-Spline-based vs. Mesh-based Multi-Objective Deformable Image Registration
Georgios Andreadis, Joas I. Mulder, Anton Bouter +2
The transformation model is an essential component of any deformable image registration approach. It provides a representation of physical deformations between images, thereby defi…
MOREA: a GPU-accelerated Evolutionary Algorithm for Multi-Objective Deformable Registration of 3D Medical Images
Georgios Andreadis, Peter A. N. Bosman, Tanja Alderliesten
Finding a realistic deformation that transforms one image into another, in case large deformations are required, is considered a key challenge in medical image analysis. Having a p…
Evolutionary Neural Cascade Search across Supernetworks
Alexander Chebykin, Tanja Alderliesten, Peter A. N. Bosman
To achieve excellent performance with modern neural networks, having the right network architecture is important. Neural Architecture Search (NAS) concerns the automatic discovery…
Adults as Augmentations for Children in Facial Emotion Recognition with Contrastive Learning
Marco Virgolin, Andrea De Lorenzo, Tanja Alderliesten +1
Emotion recognition in children can help the early identification of, and intervention on, psychological complications that arise in stressful situations such as cancer treatment.…
Observer variation-aware medical image segmentation by combining deep learning and surrogate-assisted genetic algorithms
Arkadiy Dushatskiy, Adriënne M. Mendrik, Peter A. N. Bosman +1
There has recently been great progress in automatic segmentation of medical images with deep learning algorithms. In most works observer variation is acknowledged to be a problem a…
An End-to-end Deep Learning Approach for Landmark Detection and Matching in Medical Images
Monika Grewal, Timo M. Deist, Jan Wiersma +2
Anatomical landmark correspondences in medical images can provide additional guidance information for the alignment of two images, which, in turn, is crucial for many medical appli…