623-HoloTea: 3D Flow Matching for Volumetric Transcriptomics
The paper introduces HoloTea, a novel computational framework designed to generate 3D volumetric tissue gene expression profiles from serial histology images. While traditional methods often analyze tissue slices in isolation, this model ensures anatomical continuity by retrieving morphologically similar data from adjacent sections to inform its predictions. The system utilizes a scalable flow-matching architecture and biology-aligned ZINB priors to accurately capture the complex nature of transcript count data. By leveraging global attention mechanisms, it remains efficient enough to process…
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