91 citations · 160 across the 9 of their papers we have counts for
7 papers · 1 filter
Hybrid graph convolutional neural networks for landmark-based anatomical segmentation
Nicolás Gaggion, Lucas Mansilla, Diego Milone +1
In this work we address the problem of landmark-based segmentation for anatomical structures. We propose HybridGNet, an encoder-decoder neural architecture which combines standard…
Orthogonal Ensemble Networks for Biomedical Image Segmentation
Agostina J. Larrazabal, César Martínez, Jose Dolz +1
Despite the astonishing performance of deep-learning based approaches for visual tasks such as semantic segmentation, they are known to produce miscalibrated predictions, which cou…
Cranial Implant Design via Virtual Craniectomy with Shape Priors
Franco Matzkin, Virginia Newcombe, Ben Glocker +1
Cranial implant design is a challenging task, whose accuracy is crucial in the context of cranioplasty procedures. This task is usually performed manually by experts using computer…
Unsupervised Domain Adaptation via CycleGAN for White Matter Hyperintensity Segmentation in Multicenter MR Images
Julian Alberto Palladino, Diego Fernandez Slezak, Enzo Ferrante
Automatic segmentation of white matter hyperintensities in magnetic resonance images is of paramount clinical and research importance. Quantification of these lesions serve as a pr…
Self-supervised Skull Reconstruction in Brain CT Images with Decompressive Craniectomy
Franco Matzkin, Virginia Newcombe, Susan Stevenson +6
Decompressive craniectomy (DC) is a common surgical procedure consisting of the removal of a portion of the skull that is performed after incidents such as stroke, traumatic brain…
Learning Deformable Registration of Medical Images with Anatomical Constraints
Lucas Mansilla, Diego H. Milone, Enzo Ferrante
Deformable image registration is a fundamental problem in the field of medical image analysis. During the last years, we have witnessed the advent of deep learning-based image regi…