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Quantitative CMR population imaging on 20, 000 subjects of the UK Biobank imaging study: LV/RV quantification pipeline and its evaluation.

, , , , , , , , , , , , , , , and . Medical Image Analysis, (2019)

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Improving the generalizability of convolutional neural network-based segmentation on CMR images., , , , , , , , , and 6 other author(s). CoRR, (2019)Quantitative CMR population imaging on 20, 000 subjects of the UK Biobank imaging study: LV/RV quantification pipeline and its evaluation., , , , , , , , , and 6 other author(s). Medical Image Analysis, (2019)Human-level CMR image analysis with deep fully convolutional networks., , , , , , , , , and 13 other author(s). CoRR, (2017)Real-Time Prediction of Segmentation Quality., , , , , , , , , and 10 other author(s). MICCAI (4), volume 11073 of Lecture Notes in Computer Science, page 578-585. Springer, (2018)End-Diastolic and End-Systolic LV Morphology in the Presence of Cardiovascular Risk Factors: A UK Biobank Study., , , , , , and . FIMH, volume 11504 of Lecture Notes in Computer Science, page 304-312. Springer, (2019)Towards the Creation of the Cardiovascular Magnetic Resonance Quality Assessment Ontology (CMR-QA)., , , , , , , , , and 1 other author(s). SWAT4LS, volume 1795 of CEUR Workshop Proceedings, CEUR-WS.org, (2016)Towards the Semantic Enrichment of Free-Text Annotation of Image Quality Assessment for UK Biobank Cardiac Cine MRI Scans., , , , , , , , , and 1 other author(s). LABELS/DLMIA@MICCAI, volume 10008 of Lecture Notes in Computer Science, page 238-248. (2016)Automated Quality Control in Image Segmentation: Application to the UK Biobank Cardiac MR Imaging Study., , , , , , , , , and 12 other author(s). CoRR, (2019)Quality Control-Driven Image Segmentation Towards Reliable Automatic Image Analysis in Large-Scale Cardiovascular Magnetic Resonance Aortic Cine Imaging., , , , , , , , , and 9 other author(s). MICCAI (2), volume 11765 of Lecture Notes in Computer Science, page 750-758. Springer, (2019)Emergence of Familiness and Family Owned Business Performance: The Case of Myanmar., and . IJABIM, 10 (3): 61-73 (2019)