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20172023
most citedImproving the generalizability of convolutional neural network-based segmentation on CMR images

127 citations · 270 across the 13 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

eess.IV2019★ 20 cited

Joint Motion Estimation and Segmentation from Undersampled Cardiac MR Image

Chen Qin, Wenjia Bai, Jo Schlemper +4

Accelerating the acquisition of magnetic resonance imaging (MRI) is a challenging problem, and many works have been proposed to reconstruct images from undersampled k-space data. H…

eess.IV2019★ 127 cited

Improving the generalizability of convolutional neural network-based segmentation on CMR images

Chen Chen, Wenjia Bai, Rhodri H. Davies +13

Convolutional neural network (CNN) based segmentation methods provide an efficient and automated way for clinicians to assess the structure and function of the heart in cardiac MR…

eess.IV2019

3D Cardiac Shape Prediction with Deep Neural Networks: Simultaneous Use of Images and Patient Metadata

Rahman Attar, Marco Pereanez, Christopher Bowles +4

Large prospective epidemiological studies acquire cardiovascular magnetic resonance (CMR) images for pre-symptomatic populations and follow these over time. To support this approac…

cs.CV2019★ 1 cited

Automated Quality Control in Image Segmentation: Application to the UK Biobank Cardiac MR Imaging Study

Robert Robinson, Vanya V. Valindria, Wenjia Bai +19

Background: The trend towards large-scale studies including population imaging poses new challenges in terms of quality control (QC). This is a particular issue when automatic proc…

eess.IV2019★ 1 cited

High Throughput Computation of Reference Ranges of Biventricular Cardiac Function on the UK Biobank Population Cohort

Rahman Attar, Marco Pereanez, Ali Gooya +6

The exploitation of large-scale population data has the potential to improve healthcare by discovering and understanding patterns and trends within this data. To enable high throug…