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20172019
most citedLearning-Based Quality Control for Cardiac MR Images

68 citations · 74 across the 5 of their papers we have counts for

collaborators

5 papers

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…

cs.CV2018

A Comprehensive Approach for Learning-based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks

Giacomo Tarroni, Ozan Oktay, Matthew Sinclair +7

In the clinical routine, short axis (SA) cine cardiac MR (CMR) image stacks are acquired during multiple subsequent breath-holds. If the patient cannot consistently hold the breath…

cs.CV2018★ 1 cited

Recurrent neural networks for aortic image sequence segmentation with sparse annotations

Wenjia Bai, Hideaki Suzuki, Chen Qin +4

Segmentation of image sequences is an important task in medical image analysis, which enables clinicians to assess the anatomy and function of moving organs. However, direct applic…

cs.CV2018★ 68 cited

Learning-Based Quality Control for Cardiac MR Images

Giacomo Tarroni, Ozan Oktay, Wenjia Bai +9

The effectiveness of a cardiovascular magnetic resonance (CMR) scan depends on the ability of the operator to correctly tune the acquisition parameters to the subject being scanned…

cs.CV2017★ 4 cited

Automated cardiovascular magnetic resonance image analysis with fully convolutional networks

Wenjia Bai, Matthew Sinclair, Giacomo Tarroni +20

Cardiovascular magnetic resonance (CMR) imaging is a standard imaging modality for assessing cardiovascular diseases (CVDs), the leading cause of death globally. CMR enables accura…