The authors introduce a 3D CT-based visual question answering benchmark with six error types and three task levels, and show that current 3D medical MLLMs perform poorly on it.
Comparing diagnostic accuracy of radiolo- gists versus gpt-4v and gemini pro vision using image inputs from diagnosis please cases.Radiology, 312(1), July 2024
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MedErr-CT: A Visual Question Answering Benchmark for Identifying and Correcting Errors in CT Reports
The authors introduce a 3D CT-based visual question answering benchmark with six error types and three task levels, and show that current 3D medical MLLMs perform poorly on it.