Radiological AGI: How Close Are We?
summary
An agentic pipeline calls a toolbox of mocked tools (simulated perfect detectors and measurers) and is evaluated on the PARROT dataset with the RadMatch framework. A realistic 1,000-tool setup yields RadMatch actionable recall 17%; an infinite-tool pipeline 67% recall. The gap comes from missed natural-language characterizations (complex descriptions of location/appearance) that require vision‑language models and robust tool-VLM coordination rather than more narrowly focused detectors.
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chapters (6)
- 0:00Radiologist workflow intro
- 2:40Radiology tools limitations
- 4:06Vision language model limits
- 5:11Agentic pipeline design
- 7:17Evaluating agent with RAD match
- 9:49Radiological AGI future
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