Deep learning models for medical image segmentation can fail unexpectedly and spectacularly for pathological cases and images acquired at different centers than training images, with labeling errors that violate expert knowledge. Such errors undermine the trustworthiness of deep learning models for...
Détails bibliographiques
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 5 vom: 10. Mai, Seite 3784-3795
|
|---|
| Auteur principal: |
Fidon, Lucas
(Auteur) |
|---|
| Autres auteurs: |
Aertsen, Michael,
Kofler, Florian,
Bink, Andrea,
David, Anna L,
Deprest, Thomas,
Emam, Doaa,
Guffens, Frederic,
Jakab, Andras,
Kasprian, Gregor,
Kienast, Patric,
Melbourne, Andrew,
Menze, Bjoern,
Mufti, Nada,
Pogledic, Ivana,
Prayer, Daniela,
Stuempflen, Marlene,
Van Elslander, Esther,
Ourselin, Sebastien,
Deprest, Jan,
Vercauteren, Tom |
|---|
| Format: | Article en ligne
|
|---|
| Langue: | English |
|---|
| Publié: |
2024
|
|---|
| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence
|
|---|
| Sujets: | Journal Article
Research Support, Non-U.S. Gov't |
|---|