Quantification of common carotid artery and descending aorta vessel wall thickness from MR vessel wall imaging using a fully automated processing pipeline.

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Learning-based automated segmentation of the carotid artery vessel wall in dual-sequence MRI using subdivision surface fitting.

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P2860

Quantification of common carotid artery and descending aorta vessel wall thickness from MR vessel wall imaging using a fully automated processing pipeline.

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2016 nî lūn-bûn

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Quantification of common carot ...... automated processing pipeline.

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Quantification of common carot ...... automated processing pipeline.

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Quantification of common carot ...... automated processing pipeline.

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Albert de Roos

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Anne Brandts

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Jos J M Westenberg

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Reza Alizadeh Dehnavi

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Ronald van 't Klooster

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Shan Gao

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Stijntje D Roes

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P2860

G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences

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Predictors of carotid atherosclerotic plaque progression as measured by noninvasive magnetic resonance imaging.

MRI of atherosclerosis in clinical trials.

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Aortic vessel wall magnetic resonance imaging at 3.0 Tesla: a reproducibility study of respiratory navigator gated free-breathing 3D black blood magnetic resonance imaging

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Intracranial vessel wall imaging at 7.0-T MRI.

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215-228

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scholarly article

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10.1002/JMRI.25332

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Rob J van der Geest

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2016-06-02T00:00:00Z

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automation

Quantification of common carotid artery and descending aorta vessel wall thickness from MR vessel wall imaging using a fully automated processing pipeline.

about

P2860

P2860

Quantification of common carotid artery and descending aorta vessel wall thickness from MR vessel wall imaging using a fully automated processing pipeline.

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