magnetic_resonance_imaging_for_intracranial_metastases_multicenter_studies

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magnetic_resonance_imaging_for_intracranial_metastases_multicenter_studies [2025/06/25 06:54] – administradormagnetic_resonance_imaging_for_intracranial_metastases_multicenter_studies [2025/06/25 06:54] (current) – administrador
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     - St. Nikolaus Hospital, Eupen & Ghent University, Ghent (Belgium)       - St. Nikolaus Hospital, Eupen & Ghent University, Ghent (Belgium)  
     - Netherlands Cancer Institute, Amsterdam (Netherlands)       - Netherlands Cancer Institute, Amsterdam (Netherlands)  
-published in the Radiology  Journal +published in the [[Radiology Journal]] 
 to develop a generalizable deep‑learning system for detection, segmentation, and longitudinal tracking of brain metastases (BMs) of any size on MRI.  to develop a generalizable deep‑learning system for detection, segmentation, and longitudinal tracking of brain metastases (BMs) of any size on MRI. 
 The model achieved high sensitivity (98.0% internal, 97.4% external; 93.3% for <3 mm lesions), Dice ~0.9, minimal false positives (~0.6/patient), and robust generalizability on pre‑ and post‑treatment MRI. The model achieved high sensitivity (98.0% internal, 97.4% external; 93.3% for <3 mm lesions), Dice ~0.9, minimal false positives (~0.6/patient), and robust generalizability on pre‑ and post‑treatment MRI.
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