Fig. 1: Overview of the study.
From: A visual–omics foundation model to bridge histopathology with spatial transcriptomics
a, The workflow of pretraining the OmiCLIP model with paired image–transcriptomics dataset via contrastive learning. b, Workflow of the Loki platform using the OmiCLIP foundation model as an engine. Left diagram illustrates the size of the training data in different organs. Right diagram lists the existing modules of the Loki platform, including tissue alignment, cell-type decomposition, tissue annotation, ST gene expression prediction and histology image–transcriptomics retrieval. Created in BioRender.com. c, The heat map represents image embeddings and transcriptomic embeddings similarity across various organs and disease conditions. The color of the heat map reflects the OmiCLIP’s embedding similarities, with red indicating high similarity and blue indicating low similarity. HCM, hypertrophic cardiomyopathy; HBV, hepatitis B virus infection. d, Schematic illustration of Loki platform with transfer learning for 3D tissue analysis. Created in BioRender.com.
