Journal article
Longitudinal structural and perfusion MRI enhanced by machine learning outperforms standalone modalities and radiological expertise in high-grade glioma surveillance
- Abstract:
- Our results indicate that utilisation of a machine learning (SVM) classifier based on analysis of longitudinal perfusion time points and combined structural and perfusion features significantly enhances classification outcome (p value= 0.0001).
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Version of record, pdf, 658.2KB, Terms of use)
-
- Publisher copy:
- 10.1007/s00234-021-02719-6
Authors
- Publisher:
- Springer
- Journal:
- Neuroradiology More from this journal
- Volume:
- 63
- Issue:
- 12
- Pages:
- 2047-2056
- Publication date:
- 2021-05-28
- DOI:
- EISSN:
-
1432-1920
- ISSN:
-
0028-3940
- Language:
-
English
- Keywords:
- Pubs id:
-
1181895
- Local pid:
-
pubs:1181895
- Source identifiers:
-
W3165650936
- Deposit date:
-
2026-03-24
- ARK identifier:
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.
Terms of use
- Copyright date:
- 2021
- Licence:
- CC Attribution (CC BY)
If you are the owner of this record, you can report an update to it here: Report update to this record