Development and routine implementation of deep learning algorithm for automatic brain metastases segmentation on MRI for RANO-BM criteria follow-up

Development and routine implementation of deep learning algorithm for automatic brain metastases segmentation on MRI for RANO-BM criteria follow-up

Rationale and objectives: The RANO-BM criteria, which employ a one-dimensional measurement of the largest diameter, are imperfect due to the fact that the lesion volume is neither isotropic nor homogeneous. Furthermore, this approach is inherently time-consuming. Consequently, in clinical practice,...

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Bibliographic Details
Main Authors: Loïse Dessoude, Raphaëlle Lemaire, Romain Andres, Thomas Leleu, Alexandre G. Leclercq, Alexis Desmonts, Typhaine Corroller, Amirath Fara Orou-Guidou, Luca Laduree, Loic Le Henaff, Joëlle Lacroix, Alexis Lechervy, Dinu Stefan, Aurélien Corroyer-Dulmont
Format: Article
Language:English
Published: Elsevier 2025-02-01
Series:NeuroImage
Subjects:
Deep learning
Radiology
Brain metastases
RANO-BM
Clinical routine
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811925000023
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