Work

Accelerating dynamic imaging of the lung using blind compressed sensing

Year: 2014

Type: article

Abstract: Background Real time dynamic lung MRI is a promising tool to noninvasively assess lung function and mechanics. However, it potential is not realized in the clinic due to the restricted spatio-temporal resolution and volume coverage. The main focus of this work is to overcome these drawbacks using the recent blind compressed sensing (BCS) scheme [Lingala et al., IEEE TMI 2013], which enables recovery from undersampled k-t measurements.

Source: Journal of Cardiovascular Magnetic Resonance

DOI: 10.1186/1532-429x-16-s1-w27

Authors: Sajan Goud Lingala, Yasir Mohsin, John D Newell, Jessica C Sieren, Daniel Thedens, Peter Kollasch, Mathews Jacob

Institution: University of Iowa

Language: English

Topic: Advanced MRI Techniques and Applications

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,000

Funders: National Science Foundation, American Heart Association, National Institutes of Health, National Heart, Lung, and Blood Institute

Awards: G2229765156, Novel algorithm for improved contrast enhanced cardiac MRI, CAREER: Efficient Image Sparsifying Operators: Theory, Algorithms and Applications, CIF: Small: Adaptive signal representation for accelerated multidimensional imaging

OpenAlex ID: W2090590460

FWCI: 0.261

Cites:

Cited by: 1

Related to: 10