HEMIT: H&E to Multiplex-immunohistochemistry Image Translation with Dual-Branch Pix2pix Generator
<|reference_start|>HEMIT: H&E to Multiplex-immunohistochemistry Image Translation with Dual-Branch Pix2pix Generator: Computational analysis of multiplexed immunofluorescence histology data is emerging as an important method for understanding the tumour micro-environment in cancer. This work presents HEMIT, a dataset designed for translating Hematoxylin and Eosin (H&E) sections to multiplex-immunohistochemistry (mIHC) images, featuring DAPI, CD3, and panCK markers. Distinctively, HEMIT's mIHC images are multi-component and cellular-level aligned with H&E, enriching supervised stain translation tasks. To our knowledge, HEMIT is the first publicly available cellular-level aligned dataset that enables H&E to multi-target mIHC image translation. This dataset provides the computer vision community with a valuable resource to develop novel computational methods which have the potential to gain new insights from H&E slide archives.   We also propose a new dual-branch generator architecture, using residual Convolutional Neural Networks (CNNs) and Swin Transformers which achieves better translation outcomes than other popular algorithms. When evaluated on HEMIT, it outperforms pix2pixHD, pix2pix, U-Net, and ResNet, achieving the highest overall score on key metrics including the Structural Similarity Index Measure (SSIM), Pearson correlation score (R), and Peak signal-to-noise Ratio (PSNR). Additionally, downstream analysis has been used to further validate the quality of the generated mIHC images. These results set a new benchmark in the field of stain translation tasks.<|reference_end|>
@article{bian2024hemit:,
    title={HEMIT: H&E to Multiplex-immunohistochemistry Image Translation with
  Dual-Branch Pix2pix Generator},
    author={Chang Bian, Beth Philips, Tim Cootes, Martin Fergie},
    journal={arXiv preprint arXiv:2403.18501},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.18501},
    primaryClass={eess.IV cs.CV}
}