AI Summary

Researchers highlight that MRI remains a leading tool for diagnosing and monitoring brain tumors, yet current clinical practice often relies on subjective or two‑dimensional measurements that can miss the true extent of irregularly growing tumors such as meningiomas. Studies cited show three‑dimensional spatial analysis yields a more accurate assessment of tumor burden. While deep neural networks can automatically segment tumors in 3D, the inherent uncertainty of these AI outputs—varying with tumor characteristics, location, and image quality—reduces clinician confidence and limits adoption. The authors argue that measuring and communicating this uncertainty is essential for improving trust in AI‑enhanced brain‑tumor imaging.

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