Feasibility of a sub-3-minute imaging strategy for ungated quiescent interval slice-selective MRA of the extracranial carotid arteries using radial k-space sampling and deep learning-based image processing.

Journal: Magnetic resonance in medicine

PMID: 31975432

Abstract

PURPOSE: To develop and test the feasibility of a sub-3-minute imaging strategy for non-contrast evaluation of the extracranial carotid arteries using ungated quiescent interval slice-selective (QISS) MRA, combining single-shot radial sampling with deep neural network-based image processing to optimize image quality.

Authors

Ioannis Koktzoglou

Department of Radiology, NorthShore University HealthSystem, Evanston, Illinois.
Rong Huang

School of Nursing, Chuanbei Medical College, Nanchong, China.
Archie L Ong

Pritzker School of Medicine, University of Chicago, Chicago, Illinois.
Pascale J Aouad

Department of Radiology, NorthShore University HealthSystem, Evanston, Illinois.
Emily A Aherne

Department of Radiology, NorthShore University HealthSystem, Evanston, Illinois.
Robert R Edelman

Department of Radiology, NorthShore University HealthSystem, Evanston, Illinois.

Keywords

Carotid Arteries Deep Learning Feasibility Studies Humans Image Interpretation, Computer-Assisted Magnetic Resonance Angiography

External Resources

View on PubMed Access via DOI PubMed (31975432)

Feasibility of a sub-3-minute imaging strategy for ungated quiescent interval slice-selective MRA of the extracranial carotid arteries using radial k-space sampling and deep learning-based image processing.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals