Machine learning in cardiovascular magnetic resonance: basic concepts and applications
Abstract Machine learning (ML) is making a dramatic impact on cardiovascular magnetic resonance (CMR) in many ways. This review seeks to highlight the major areas in CMR where ML, and deep learning in particular, can assist clinicians and engineers in improving imaging efficiency, quality, image ana...
Main Authors: | Tim Leiner, Daniel Rueckert, Avan Suinesiaputra, Bettina Baeßler, Reza Nezafat, Ivana Išgum, Alistair A. Young |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2019-10-01
|
Series: | Journal of Cardiovascular Magnetic Resonance |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s12968-019-0575-y |
Similar Items
-
Deep Learning Radiomics to Predict PTEN Mutation Status From Magnetic Resonance Imaging in Patients With Glioma
by: Hongyu Chen, et al.
Published: (2021-10-01) -
Radiomics Signatures of Cardiovascular Risk Factors in Cardiac MRI: Results From the UK Biobank
by: Irem Cetin, et al.
Published: (2020-11-01) -
Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification
by: Alex Bratt, et al.
Published: (2019-01-01) -
Associations of Meat and Fish Consumption With Conventional and Radiomics Cardiovascular Magnetic Resonance Phenotypes in the UK Biobank
by: Zahra Raisi-Estabragh, et al.
Published: (2021-05-01) -
Machine learning applications in prostate cancer magnetic resonance imaging
by: Renato Cuocolo, et al.
Published: (2019-08-01)