Addressing the Generalizability of AI in Radiology Using a Novel Data Augmentation Framework with Synthetic Patient Image Data: Proof-of-Concept and External Validation for Classification Tasks in Multiple Sclerosis
Gianluca Brugnara, Chandrakanth Jayachandran Preetha, Katerina Deike, Robert Haase, Thomas Pinetz, Martha Foltyn-Dumitru, Mustafa A. Mahmutoglu, Brigitte Wildemann, Ricarda Diem, Wolfgang Wick, Alexander Radbruch, Martin Bendszus, Hagen Meredig, Aditya Rastogi, Philipp Vollmuth
Source abstract
Generative adversarial network–based synthetic data augmentation during model training substantially improved performance of artificial intelligence models when applied to external MRI data and may be extended to a variety of clinical tasks to reduce domain shift on unseen data.
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