Precise cell recovery by cell nucleus united transcript (CellCUT) for enhanced spatial transcriptomics

Abstract excerpt

Cell segmentation is the first step in parsing spatial transcriptomic data, often a challenging task. Existing cell segmentation methods do not fully leverage spatial cues between nuclear images and transcripts, tending to produce undesirable cell profiles for densely packed cells. Here, we propose CellCUT to perform cell segmentation and transcript assignment without additional manual annotations. CellCUT provide...

Topics

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• Algorithms
• Cell Line
• Cell Nucleus
• Deep Learning
• Image Processing, Computer-Assisted
• Machine Learning
• Neural Networks, Computer
• Phenotype

Identifiers and source

Literature Corpus work

ea495e6f-23f3-568a-aea9-94564c67270e

DOI

10.1101/2024.05.28.596350