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June 30, 2024

MuCST: restoring and integrating heterogeneous morphology images and spatial transcriptomics data with contrastive learning

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YWYu WangXMXiaoke Ma

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Cite This Study

Wang et al. (2024) studied this question.

synapsesocial.com/papers/68e626b1b6db6435875b96efhttps://doi.org/10.1101/2024.06.26.600708
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1MuST: multiple-modality structure transformation for single-cell spatial transcriptomics2025
  2. 2A multi-view graph contrastive learning framework for deciphering spatially resolved transcriptomics data2024 · 11 citations
  3. 3Spatial transcriptomics expression prediction from histopathology based on cross-modal mask reconstruction and contrastive learning2025 · 2 citations
  4. 4ViMST: vision transformer-based dual modality multi-task graph contrastive network for spatial transcriptomics microenvironments investigation2026
  5. 5Denoising spatially resolved transcriptomics with consistency of heterogeneous spatial coordinates, transcription, and morphology2025