Two new technical reports detail advancements in radiology foundation models. One review paper analyzes 67 studies on vision foundation models (VFMs) in radiology, highlighting the prevalence of transformer architectures and self-supervised pretraining, but noting inconsistencies in evaluation and reporting. The other report introduces Harrison.Rad 1.5, a multimodal large language model specifically designed for radiology, which has demonstrated the ability to draft reports from images and clinical context, even meeting simulated professional examination standards. AI
IMPACT These advancements suggest improved efficiency and accuracy in radiological report generation, potentially alleviating workforce shortages.
RANK_REASON Two technical reports detailing new research in AI for radiology.
- Angoff-method thresholds
- arXiv
- FRCR 2B Short Case
- Harrison.Rad 1.5
- Hugging Face
- RadGraph-XL
- ReXgradient
- FRCR 2B Short Case examination
- PRISMAScR
- Radiology
- Transformer
- Vision Foundation Models
- Xavier Rafael-Palou
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