Preclinical MRI to quantify pulmonary disease severity and trajectories in poorly characterized mouse models: A pedagogical example using data from novel transgenic models of lung fibrosis

Preclinical MRI to quantify pulmonary disease severity and trajectories in poorly characterized mouse models: A pedagogical example using data from novel transgenic models of lung fibrosis

Structural remodeling in lung disease is progressive and heterogeneous, making temporally and spatially explicit information necessary to understand disease initiation and progression. While mouse models are essential to elucidate mechanistic pathways underlying disease, the experimental tools commo...

Full description

Bibliographic Details
Main Authors: Ian R. Stecker, Matthew S. Freeman, Sneha Sitaraman, Chase S. Hall, Peter J. Niedbalski, Alexandra J. Hendricks, Emily P. Martin, Timothy E. Weaver, Zackary I. Cleveland
Format: Article
Language:English
Published: Elsevier 2021-06-01
Series:Journal of Magnetic Resonance Open
Subjects:
Preclincial imaging
Retrospective gating
Machine learning (deep-learning)
Ultrashort echo time (UTE)
Pulmonary fibrosis
Online Access:http://www.sciencedirect.com/science/article/pii/S2666441021000042

Internet

http://www.sciencedirect.com/science/article/pii/S2666441021000042

Similar Items