DeLTA: Automated cell segmentation, tracking, and lineage reconstruction using deep learning

Volume: 16, Issue: 4, Pages: e1007673 - e1007673
Published: Apr 13, 2020
Abstract
Microscopy image analysis is a major bottleneck in quantification of single-cell microscopy data, typically requiring human oversight and curation, which limit both accuracy and throughput. To address this, we developed a deep learning-based image analysis pipeline that performs segmentation, tracking, and lineage reconstruction. Our analysis focuses on time-lapse movies of Escherichia coli cells trapped in a "mother machine" microfluidic...
Paper Details
Title
DeLTA: Automated cell segmentation, tracking, and lineage reconstruction using deep learning
Published Date
Apr 13, 2020
Volume
16
Issue
4
Pages
e1007673 - e1007673
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