Medical AI Models Battle It Out—And the Winner Might Surprise You

This article evaluates retrieval recall across multiple AI models for medical imaging, including DreamSim, ResNet50, and DINO variants. It compares slice-wise, volume-based, region-based, and localized retrieval methods on both coarse (29) and fine-grained (104) anatomical structures. Results show DreamSim excels at slice-wise and region-based recall, ResNet50 performs best at coarse volume retrieval, while DINO models lead in localized and fine-grained recall. The study highlights trade-offs between model types and retrieval approaches, underscoring the importance of context, granularity, and localization in advancing medical AI retrieval systems.