Automated quality control in image segmentation: application to the UK Biobank cardiovascular magnetic resonance imaging study

Automated quality control in image segmentation: application to the UK Biobank cardiovascular magnetic resonance imaging study

Abstract 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 processing tools such as image segmentation methods are employed to derive quantitative measures or biomarkers for f...

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Bibliographic Details
Main Authors: Robert Robinson, Vanya V. Valindria, Wenjia Bai, Ozan Oktay, Bernhard Kainz, Hideaki Suzuki, Mihir M. Sanghvi, Nay Aung, José Miguel Paiva, Filip Zemrak, Kenneth Fung, Elena Lukaschuk, Aaron M. Lee, Valentina Carapella, Young Jin Kim, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Chris Page, Paul M. Matthews, Daniel Rueckert, Ben Glocker
Format: Article
Language:English
Published: Elsevier 2019-03-01
Series:Journal of Cardiovascular Magnetic Resonance
Subjects:
Automatic quality control
Population imaging
Segmentation
Online Access:http://link.springer.com/article/10.1186/s12968-019-0523-x

Internet

http://link.springer.com/article/10.1186/s12968-019-0523-x

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