430 citations · 722 across the 13 of their papers we have counts for
9 papers · 1 filter
Atlas-ISTN: Joint Segmentation, Registration and Atlas Construction with Image-and-Spatial Transformer Networks
Matthew Sinclair, Andreas Schuh, Karl Hahn +5
Deep learning models for semantic segmentation are able to learn powerful representations for pixel-wise predictions, but are sensitive to noise at test time and do not guarantee a…
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…
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…
Image-level Harmonization of Multi-Site Data using Image-and-Spatial Transformer Networks
R. Robinson, Q. Dou, D. C. Castro +5
We investigate the use of image-and-spatial transformer networks (ISTNs) to tackle domain shift in multi-site medical imaging data. Commonly, domain adaptation (DA) is performed wi…
Deep Generative Model-based Quality Control for Cardiac MRI Segmentation
Shuo Wang, Giacomo Tarroni, Chen Qin +7
In recent years, convolutional neural networks have demonstrated promising performance in a variety of medical image segmentation tasks. However, when a trained segmentation model…
Causality matters in medical imaging
Daniel C. Castro, Ian Walker, Ben Glocker
This article discusses how the language of causality can shed new light on the major challenges in machine learning for medical imaging: 1) data scarcity, which is the limited avai…