Automated Cell Lineage Reconstruction using Label-Free 4D Microscopy

Here we describe embGAN, a deep learning pipeline that addresses the challenge of automated cell detection and tracking in label-free 3D time lapse imaging. embGAN requires no manual data annotation for training, learns robust detections that exhibits a high degree of scale invariance and generalize...

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Bibliographic Details
Published inbioRxiv
Main Authors Waliman, Matthew, Johnson, Ryan L, Natesan, Gunalan, Tan, Shiqin, Santella, Anthony, Hong, Ray L, Shah, Pavak K
Format Journal Article Paper
LanguageEnglish
Published United States Cold Spring Harbor Laboratory Press 22.01.2024
Subjects
Cell lineage
Deep learning
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Summary:Here we describe embGAN, a deep learning pipeline that addresses the challenge of automated cell detection and tracking in label-free 3D time lapse imaging. embGAN requires no manual data annotation for training, learns robust detections that exhibits a high degree of scale invariance and generalizes well to images acquired in multiple labs on multiple instruments.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Working Paper/Pre-Print-1
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ISSN:2692-8205
2692-8205
DOI:10.1101/2024.01.20.576449