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The aim is to analyze spatial hallucination phenomena in radiology visual question answering.

May 6, 2026Open Access

Spatially-Grounded Hallucination Detection in Multimodal Medical AI: A Study of Vision-Language Models on Radiology Visual Question Answering

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The aim is to analyze spatial hallucination phenomena in radiology visual question answering.
Introduced a four-tier taxonomy of medical spatial hallucinations
Analyzed 14 vision-language models across six radiology visual question answering benchmarks
Evaluated spatial grounding fidelity using established metrics and a new composite metric
Spatial hallucination rates in radiology tasks ranged from 23.7% to 41.2%
These rates significantly exceed the 12.4%–18.9% observed on natural image benchmarks
Proposed mitigation strategies for enhancing spatial fidelity in multimodal medical AI

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This research addresses spatial hallucinations in radiology visual question answering, suggesting effective taxonomy and mitigation strategies.

Pratul Mishra (2026) studied this question.

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This research addresses spatial hallucinations in radiology visual question answering, suggesting effective taxonomy and mitigation strategies.