GitHub / EliHei2 / segger_dev
a cutting-edge cell segmentation model specifically designed for single-molecule resolved spatial omics datasets. It addresses the challenge of accurately segmenting individual cells in complex imaging datasets, leveraging a unique approach based on graph neural networks (GNNs).
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EliHei2%2Fsegger_dev
PURL: pkg:github/EliHei2/segger_dev
Stars: 74
Forks: 9
Open issues: 32
License: mit
Language: HTML
Size: 12.7 MB
Dependencies parsed at: Pending
Created at: 12 months ago
Updated at: 4 days ago
Pushed at: 4 days ago
Last synced at: 4 days ago
Topics: ai, cell-segmentation, graph-neural-networks, graphs, molecule-graphs, oncology, segmentation, single-cell-analysis, spatial-omics, spatial-transcriptomics, xenium