Image reconstruction by domain-transform manifold learning

Bo Zhu, Jeremiah Z. Liu, Stephen F. Cauley, Bruce R. Rosen and Matthew S. Rosen ()
Additional contact information
Bo Zhu: A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital
Jeremiah Z. Liu: Harvard University
Stephen F. Cauley: A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital
Bruce R. Rosen: A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital
Matthew S. Rosen: A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital

Nature, 2018, vol. 555, issue 7697, 487-492

Abstract: Image reconstruction is reformulated using a data-driven, supervised machine learning framework that allows a mapping between sensor and image domains to emerge from even noisy and undersampled data, improving accuracy and reducing image artefacts.

Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://www.nature.com/articles/nature25988 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:nature:v:555:y:2018:i:7697:d:10.1038_nature25988

Ordering information: This journal article can be ordered from
https://www.nature.com/

DOI: 10.1038/nature25988

Access Statistics for this article

Nature is currently edited by Magdalena Skipper

More articles in Nature from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().