Neural implicit functions enable resolution-agnostic, deterministic virtual staining from H&E to IHC images with SOTA results and better low-data performance than patch-based GAN or diffusion methods.
arXiv preprint arXiv:2502.16872 , year=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
Latent diffusion models exhibit geometric decoupling where curvature in out-of-distribution generation is misallocated to unstable semantic boundaries instead of image details, identifying geometric hotspots as the structural cause of editing instability.
citing papers explorer
-
IMPLICITSTAINER: Resolution Agnostic Data-Efficient Virtual Staining Using Neural Implicit Functions
Neural implicit functions enable resolution-agnostic, deterministic virtual staining from H&E to IHC images with SOTA results and better low-data performance than patch-based GAN or diffusion methods.
-
Geometric Decoupling: Diagnosing the Structural Instability of Latent
Latent diffusion models exhibit geometric decoupling where curvature in out-of-distribution generation is misallocated to unstable semantic boundaries instead of image details, identifying geometric hotspots as the structural cause of editing instability.