Deep semantic lung segmentation for tracking potential pulmonary perfusion biomarkers in chronic obstructive pulmonary disease (COPD): The multi‐ethnic study of atherosclerosis COPD study-Reference-Cited by-同舟云学术

Deep semantic lung segmentation for tracking potential pulmonary perfusion biomarkers in chronic obstructive pulmonary disease (COPD): The multi‐ethnic study of atherosclerosis COPD study

Published:2019-07-05 Issue:2 Volume:51 Page:571-579
ISSN:1053-1807
Container-title:Journal of Magnetic Resonance Imaging
language:en
Short-container-title:J. Magn. Reson. Imaging

Author:

Winther Hinrich B.¹^ORCID,Gutberlet Marcel¹,Hundt Christian²,Kaireit Till F.¹,Alsady Tawfik Moher¹^ORCID,Schmidt Bertil³,Wacker Frank¹⁴,Sun Yanping⁵,Dettmer Sabine¹⁴,Maschke Sabine K.¹^ORCID,Hinrichs Jan B.¹,Jambawalikar Sachin⁶,Prince Martin R.⁷^ORCID,Barr R. Graham⁵,Vogel‐Claussen Jens¹⁴

Affiliation:

1. Department of Diagnostic and Interventional Radiology Hannover Medical School Hannover Germany

2. NVIDIA AI Technology Center Luxembourg Luxembourg

3. Institute for Computer Science Johannes Gutenberg University Mainz Germany

4. Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH) Member of the German Center for Lung Research (DZL) Hannover Germany

5. Department of Medicine, College of Physicians and Surgeons Columbia University New York New York USA

6. Department of Radiology Columbia University Medical Center New York New York USA

7. Cornell Cardiovascular Magnetic Resonance Imaging Laboratory, Radiology Department Weill Medical College of Cornell University New York New York USA

Funder

Deutsche Forschungsgemeinschaft

National Center for Advancing Translational Sciences

National Heart, Lung, and Blood Institute

Publisher

Wiley

Subject

Radiology Nuclear Medicine and imaging

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jmri.26853

Reference39 articles.

1. Pathogenesis of chronic obstructive pulmonary disease