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20172023
most citedLearning Deformable Registration of Medical Images with Anatomical Constraints

91 citations · 165 across the 11 of their papers we have counts for

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Showing 2020Show all

5 papers · 1 filter

eess.IV2020

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…

eess.IV20201 cited

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…

eess.IV2020

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…

cs.CV20201 cited

Post-DAE: Anatomically Plausible Segmentation via Post-Processing with Denoising Autoencoders

Agostina J Larrazabal, César Martínez, Ben Glocker +1

We introduce Post-DAE, a post-processing method based on denoising autoencoders (DAE) to improve the anatomical plausibility of arbitrary biomedical image segmentation algorithms.…

eess.IV202091 cited

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…