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However, decoding spatial heterogeneity requires robust multimodal data integration that unifies gene expression, spatial positions, and histopathological images to overcome modality\u2010specific biases. Here, we propose M\u2010STGCN, a multimodal unsupervised framework that constructs a spatial weight matrix from spatial coordinates to simultaneously refine both gene expression profiles and image features, by which we establish position\u2010aware feature enhancement served as a core innovation before graph fusion. Verified on human brain and breast cancer datasets, M\u2010STGCN significantly improves the accuracy of spatial domain identification. Ablation studies confirm the importance of its position\u2010aware and image modality integration. For ST platforms lacking images and at diverse resolutions, M\u2010STGCN maintains robust performance utilizing only gene expression and spatial coordinates. By\u00a0effectively denoising raw spatial transcriptomic profiles, our approach identifies more significant spatial domain marker genes, as well as potential prognostic biomarkers for breast cancer. Moreover, M\u2010STGCN reveals that image features and spatial information contribute equally to breast cancer analysis, underscoring the critical role of image features. As a versatile and scalable tool, M\u2010STGCN enables unbiased integration of multimodal data, facilitating the deciphering of spatial heterogeneous in complex tissues.<\/jats:p>","DOI":"10.1002\/smtd.202501812","type":"journal-article","created":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T06:38:14Z","timestamp":1769063894000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["M\u2010STGCN: A Position\u2010Aware Multimodal Graph Convolutional Framework for Joint Spatial Domain Identification and Gene Expression Denoising"],"prefix":"10.1002","volume":"10","author":[{"given":"Xin","family":"Chen","sequence":"first","affiliation":[{"name":"School of Automation Guangdong University of Technology  Guangzhou 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