activity
20132022
most citedNeuromorphologicaly-preserving Volumetric data encoding using VQ-VAE

12 citations · 35 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2022★ 11 cited

NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results

Eduardo Pérez-Pellitero, Sibi Catley-Chandar, Richard Shaw +85

This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conj…

cs.CV2022★ 5 cited

HDR Reconstruction from Bracketed Exposures and Events

Richard Shaw, Sibi Catley-Chandar, Ales Leonardis +1

Reconstruction of high-quality HDR images is at the core of modern computational photography. Significant progress has been made with multi-frame HDR reconstruction methods, produc…

eess.IV2021

Acquisition-invariant brain MRI segmentation with informative uncertainties

Pedro Borges, Richard Shaw, Thomas Varsavsky +5

Combining multi-site data can strengthen and uncover trends, but is a task that is marred by the influence of site-specific covariates that can bias the data and therefore any down…

eess.IV2021★ 1 cited

The role of MRI physics in brain segmentation CNNs: achieving acquisition invariance and instructive uncertainties

Pedro Borges, Richard Shaw, Thomas Varsavsky +5

Being able to adequately process and combine data arising from different sites is crucial in neuroimaging, but is difficult, owing to site, sequence and acquisition-parameter depen…

eess.IV2021★ 4 cited

A Decoupled Uncertainty Model for MRI Segmentation Quality Estimation

Richard Shaw, Carole H. Sudre, Sebastien Ourselin +2

Quality control (QC) of MR images is essential to ensure that downstream analyses such as segmentation can be performed successfully. Currently, QC is predominantly performed visua…

eess.IV2021★ 1 cited

Estimating MRI Image Quality via Image Reconstruction Uncertainty

Richard Shaw, Carole H. Sudre, Sebastien Ourselin +1

Quality control (QC) in medical image analysis is time-consuming and laborious, leading to increased interest in automated methods. However, what is deemed suitable quality for alg…

eess.IV2020★ 12 cited

Neuromorphologicaly-preserving Volumetric data encoding using VQ-VAE

Petru-Daniel Tudosiu, Thomas Varsavsky, Richard Shaw +5

The increasing efficiency and compactness of deep learning architectures, together with hardware improvements, have enabled the complex and high-dimensional modelling of medical vo…

eess.IV2020

A Heteroscedastic Uncertainty Model for Decoupling Sources of MRI Image Quality

Richard Shaw, Carole H. Sudre, Sebastien Ourselin +1

Quality control (QC) of medical images is essential to ensure that downstream analyses such as segmentation can be performed successfully. Currently, QC is predominantly performed…

cs.CL2013★ 1 cited

Question Answering Against Very-Large Text Collections

Leon Derczynski, Richard Shaw, Ben Solway +1

Question answering involves developing methods to extract useful information from large collections of documents. This is done with specialised search engines such as Answer Finder…