Automatic 3D Bi-Ventricular Segmentation of Cardiac Images by a Shape-Refined Multi- Task Deep Learning Approach.

Publication Year: 2019

DOI:
10.1109/TMI.2019.2894322

PMCID:
PMC6728160

PMID:
30676949

Journal Information

Full Title: IEEE Trans Med Imaging

Abbreviation: IEEE Trans Med Imaging

Country: Unknown

Publisher: Unknown

Language: N/A

Publication Details

Subject Category: Diagnostic Imaging

Available in Europe PMC: Yes

Available in PMC: Yes

PDF Available: No

Transparency Score
2/6
0.0% Transparent
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Data Sharing
Evidence found in paper:

"an example is given in fig 1 4 https://digital-heart org/ 5 code is publicly available at https://github com/baiwenjia/ukbb_cardiac 6 code is publicly available at https://github com/biomedia/irtk 7 code is publicly available at https://github com/baiwenjia/cimas8 http://cmictig cs ucl ac uk/research/software/software-nifty/niftyreg figure 1 illustrating the differences between a low-resolution cmr volume (top row) and a high-resolution cmr volume (bottom row)."

COI Disclosure
Evidence found in paper:

"The research was supported by the British Heart Foundation (NH/17/1/32725, RE/13/4/30184); National Institute for Health Research (NIHR) Biomedical Research Centre based at Imperial College Healthcare NHS Trust and Imperial College London; and the Medical Research Council, UK. We would like to thank Dr Simon Gibbs, Dr Luke Howard and Prof Martin Wilkins for providing the CMR image data. The TITAN Xp GPU used for this research was kindly donated by the NVIDIA Corporation."

Protocol Registration
Open Access
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Last Updated: Aug 05, 2025