5 citations · 12 across the 4 of their papers we have counts for
4 papers
Recovering high-quality FODs from a reduced number of diffusion-weighted images using a model-driven deep learning architecture
J Bartlett, C E Davey, L A Johnston +1
Fibre orientation distribution (FOD) reconstruction using deep learning has the potential to produce accurate FODs from a reduced number of diffusion-weighted images (DWIs), decrea…
Fourier-Net: Fast Image Registration with Band-limited Deformation
Xi Jia, Joseph Bartlett, Wei Chen +6
Unsupervised image registration commonly adopts U-Net style networks to predict dense displacement fields in the full-resolution spatial domain. For high-resolution volumetric imag…
U-Net vs Transformer: Is U-Net Outdated in Medical Image Registration?
Xi Jia, Joseph Bartlett, Tianyang Zhang +3
Due to their extreme long-range modeling capability, vision transformer-based networks have become increasingly popular in deformable image registration. We believe, however, that…
Structure Unbiased Adversarial Model for Medical Image Segmentation
Tianyang Zhang, Shaoming Zheng, Jun Cheng +7
Generative models have been widely proposed in image recognition to generate more images where the distribution is similar to that of the real ones. It often introduces a discrimin…