Unsupervised discovery of tissue architecture in multiplexed imaging

Abstract excerpt

Multiplexed imaging and spatial transcriptomics enable highly resolved spatial characterization of cellular phenotypes, but still largely depend on laborious manual annotation to understand higher-order patterns of tissue organization. As a result, higher-order patterns of tissue organization are poorly understood and not systematically connected to disease pathology or clinical outcomes. To address this gap, we d...

Topics

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• Cell Image Analysis Techniques
• Ecology
• Ferroptosis and cancer prognosis
• Histological Techniques
• Machine Learning
• Phenotype
• Single-cell and spatial transcriptomics

Identifiers and source

Literature Corpus work

6d561246-4b3f-5338-aee0-dc1168215ddb

DOI

10.1101/2022.03.15.484534