Article

SynSeg: Generating Synthetic Datasets for Accurate Subcellular Segmentation with U-net

2025-02-08

Abstract excerpt

Accurate segmentation of subcellular components is crucial for understanding cellular processes, but traditional methods struggle with noise and complex structures. Convolutional neural networks improve accuracy but require large, time-consuming, and biased manually annotated datasets. Here, we developed SynSeg, a pipeline that generates synthetic training data to train a U-net model for subcellular structure segm...

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Literature Corpus work: 5a79b7f0-9241-5898-a4f4-ac70b43277d0
DOI: 10.1101/2025.02.07.637194

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