mlsanityData to 7 Oct 2026

K-Stain: Keypoint-Driven Correspondence for H&E-to-IHC Virtual Staining

arXiv 2511.06709 ↗First posted 10 Nov 2025cs.CVcited by 0

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Abstract (arXiv)

Virtual staining offers a promising method for converting Hematoxylin and Eosin (H&E) images into Immunohistochemical (IHC) images, eliminating the need for costly chemical processes. However, existing methods often struggle to utilize spatial information effectively due to misalignment in tissue slices. To overcome this challenge, we leverage keypoints as robust indicators of spatial correspondence, enabling more precise alignment and integration of structural details in synthesized IHC images. We introduce K-Stain, a novel framework that employs keypoint-based spatial and semantic relationships to enhance synthesized IHC image fidelity. K-Stain comprises three main components: (1) a Hierarchical Spatial Keypoint Detector (HSKD) for identifying keypoints in stain images, (2) a Keypoint-aware Enhancement Generator (KEG) that integrates these keypoints during image generation, and (3) a Keypoint Guided Discriminator (KGD) that improves the discriminator's sensitivity to spatial details. Our approach leverages contextual information from adjacent slices, resulting in more accurate and visually consistent IHC images. Extensive experiments show that K-Stain outperforms state-of-the-art methods in quantitative metrics and visual quality.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 30 of its 46 references that are in the map. First posted on arXiv 10 Nov 2025.

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30 of 46 references.

References · 30

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18 more
  1. 2022BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pixcited by 61
  2. 2023Adaptive Supervised PatchNCE Loss for Learning H&E-to-IHC Stain Translation with Inconsistent Groundtruth Image Pairscited by 38
  3. 2022NestedFormer: Nested Modality-Aware Transformer for Brain Tumor Segmentationcited by 33
  4. 2024Cross-conditioned Diffusion Model for Medical Image to Image Translationcited by 26
  5. 2023A Robust and Interpretable Deep Learning Framework for Multi-modal Registration via Keypointscited by 25
  6. 2023Dual-Reference Source-Free Active Domain Adaptation for Nasopharyngeal Carcinoma Tumor Segmentation across Multiple Hospitalscited by 25
  7. 2024Pathological Semantics-Preserving Learning for H&E-to-IHC Virtual Stainingcited by 21
  8. 2024Serp-Mamba: Advancing High-Resolution Retinal Vessel Segmentation with Selective State-Space Modelcited by 20
  9. 2019Multi-scale Cell Instance Segmentation with Keypoint Graph based Bounding Boxescited by 17
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  11. 2023Virtual histological staining of unlabeled autopsy tissuecited by 11
  12. 2022Virtual Histological Staining of Label-Free Total Absorption Photoacoustic Remote Sensing (TA-PARS)cited by 10
  13. 2023Structural Cycle GAN for Virtual Immunohistochemistry Staining of Gland Markers in the Coloncited by 10
  14. 2020Volumetric landmark detection with a multi-scale shift equivariant neural networkcited by 9
  15. 2023Keypoint-Augmented Self-Supervised Learning for Medical Image Segmentation with Limited Annotationcited by 7
  16. 2020Gaussian kernel smoothingcited by 6
  17. 2024StainFuser: Controlling Diffusion for Faster Neural Style Transfer in Multi-Gigapixel Histology Imagescited by 6
  18. 2022HistoStarGAN: A Unified Approach to Stain Normalisation, Stain Transfer and Stain Invariant Segmentation in Renal Histopathologycited by 3

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