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Cross-modal Diffusion Modelling for Super-resolved Spatial Transcriptomics
April 22, 2024, 4:42 a.m. | Xiaofei Wang, Xingxu Huang, Stephen J. Price, Chao Li
cs.LG updates on arXiv.org arxiv.org
Abstract: The recent advancement of spatial transcriptomics (ST) allows to characterize spatial gene expression within tissue for discovery research. However, current ST platforms suffer from low resolution, hindering in-depth understanding of spatial gene expression. Super-resolution approaches promise to enhance ST maps by integrating histology images with gene expressions of profiled tissue spots. However, current super-resolution methods are limited by restoration uncertainty and mode collapse. Although diffusion models have shown promise in capturing complex interactions between multi-modal …
abstract advancement arxiv cs.cv cs.lg current diffusion discovery eess.iv gene however images low maps modal modelling platforms q-bio.qm research resolution spatial type understanding
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