A multi-sequences MRI deep framework study applied to glioma classfication
| dc.contributor.author | Matthieu Coupet | |
| dc.contributor.author | Thierry Urruty | |
| dc.contributor.author | Teerapong Leelanupab | |
| dc.contributor.author | Mathieu Naudin | |
| dc.contributor.author | Pascal Bourdon | |
| dc.contributor.author | Christine Fernandez Maloigne | |
| dc.contributor.author | R�my Guillevin | |
| dc.date.accessioned | 2025-07-21T06:06:43Z | |
| dc.date.issued | 2022-02-28 | |
| dc.identifier.doi | 10.1007/s11042-022-12316-1 | |
| dc.identifier.uri | https://dspace.kmitl.ac.th/handle/123456789/11129 | |
| dc.subject | Interpretability | |
| dc.subject | Transfer of learning | |
| dc.subject.classification | Brain Tumor Detection and Classification | |
| dc.title | A multi-sequences MRI deep framework study applied to glioma classfication | |
| dc.type | Article |