Hallucination Detection in Virtually-Stained Histology: A Latent Space Baseline
Abstract
Histopathological analysis of stained tissue remains central to biomedical research and clinical care. Virtual staining (VS) offers a promising alternative, with potential to reduce costs and streamline workflows, yet hallucinations pose serious risks to clinical reliability. Here, we formalize the problem of hallucination detection in VS and propose a scalable post-hoc baseline method: Neural Hallucination Precursor (NHP), which explores the generator's latent space to preemptively identify hallucinations. Extensive experiments across diverse VS tasks show NHP is both effective and robust. Critically, we also find that models with fewer hallucinations do not necessarily offer better detectability, exposing a gap in current VS evaluation and underscoring the need for hallucination detection benchmarks.
Fields of Study & Subjects
Cell Image Analysis Techniques
Publication details
- Journal / source
- IEEE Transactions on Medical Imaging
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Volume
- PP
- Pages
- 1–1
- Publication date
- 1 January 2026
- Language
- EN