Deep learning-based algorithm for postoperative glioblastoma MRI segmentation: a promising new tool for tumor burden assessment

Deep learning-based algorithm for postoperative glioblastoma MRI segmentation: a promising new tool for tumor burden assessment

Show other versions (1)

Abstract Objective Clinical and surgical decisions for glioblastoma patients depend on a tumor imaging-based evaluation. Artificial Intelligence (AI) can be applied to magnetic resonance imaging (MRI) assessment to support clinical practice, surgery planning and prognostic predictions. In a real-wor...

Full description

Bibliographic Details
Main Authors: Andrea Bianconi, Luca Francesco Rossi, Marta Bonada, Pietro Zeppa, Elsa Nico, Raffaele De Marco, Paola Lacroce, Fabio Cofano, Francesco Bruno, Giovanni Morana, Antonio Melcarne, Roberta Ruda, Luca Mainardi, Pietro Fiaschi, Diego Garbossa, Lia Morra
Format: Article
Language:English
Published: SpringerOpen 2023-10-01
Series:Brain Informatics
Subjects:
Glioma
Glioblastoma
Magnetic resonance imaging
Deep learning
Machine learning
Segmentation
Online Access:https://doi.org/10.1186/s40708-023-00207-6

Internet

https://doi.org/10.1186/s40708-023-00207-6

Similar Items