FlexiCT provides CT foundation models via agglomerative pretraining on 266227 volumes from 56 datasets that match or exceed task-specific models on five task families while organizing embeddings along tumor-stage gradients.
Fabian Isensee, Paul F Jaeger, Simon AA Kohl, Jens Petersen, and Klaus H Maier-Hein
2 Pith papers cite this work, alongside 1 external citations. Polarity classification is still indexing.
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Medical foundation models match a ResNet-50 but are outperformed by radiomics (AUC 0.88) on external validation for renal lesion stratification in CT.
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Universal CT Representations from Anatomy to Disease Phenotype through Agglomerative Pretraining
FlexiCT provides CT foundation models via agglomerative pretraining on 266227 volumes from 56 datasets that match or exceed task-specific models on five task families while organizing embeddings along tumor-stage gradients.
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Benchmarking Foundation Models for Renal Lesion Stratification in CT
Medical foundation models match a ResNet-50 but are outperformed by radiomics (AUC 0.88) on external validation for renal lesion stratification in CT.