output
20212023
most citedLearning Disentangled Representations in the Imaging Domain

100 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

5 papers

eess.IV2023

Improving style transfer in dynamic contrast enhanced MRI using a spatio-temporal approach

Adam G. Tattersall, Keith A. Goatman, Lucy E. Kershaw +2

Style transfer in DCE-MRI is a challenging task due to large variations in contrast enhancements across different tissues and time. Current unsupervised methods fail due to the wid…

eess.IV2023★ 3 cited

Can a single image processing algorithm work equally well across all phases of DCE-MRI?

Adam G. Tattersall, Keith A. Goatman, Lucy E. Kershaw +2

Image segmentation and registration are said to be challenging when applied to dynamic contrast enhanced MRI sequences (DCE-MRI). The contrast agent causes rapid changes in intensi…

eess.IV2023★ 2 cited

Towards Tumour Graph Learning for Survival Prediction in Head & Neck Cancer Patients

Angel Victor Juanco Muller, Joao F. C. Mota, Keith A. Goatman +1

With nearly one million new cases diagnosed worldwide in 2020, head \& neck cancer is a deadly and common malignity. There are challenges to decision making and treatment of such c…

cs.NI2022★ 63 cited

A Look Inside 5G Standards to Support Time Synchronization for Smart Manufacturing

I. Gódor, M. Luvisotto, S. Ruffini +10

Connectivity has a major role in the current transformation of smart manufacturing. 5G is foreseen as an integral part of an end-to-end networking infrastructure supporting smart m…

cs.CV2021★ 100 cited

Learning Disentangled Representations in the Imaging Domain

Xiao Liu, Pedro Sanchez, Spyridon Thermos +2

Disentangled representation learning has been proposed as an approach to learning general representations even in the absence of, or with limited, supervision. A good general repre…