CellSeg3D, Self-supervised 3D cell segmentation for fluorescence microscopy

CellSeg3D, Self-supervised 3D cell segmentation for fluorescence microscopy

Understanding the complex three-dimensional structure of cells is crucial across many disciplines in biology and especially in neuroscience. Here, we introduce a set of models including a 3D transformer (SwinUNetR) and a novel 3D self-supervised learning method (WNet3D) designed to address the inher...

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Bibliographic Details
Main Authors: Cyril Achard, Timokleia Kousi, Markus Frey, Maxime Vidal, Yves Paychere, Colin Hofmann, Asim Iqbal, Sebastien B Hausmann, Stéphane Pagès, Mackenzie Weygandt Mathis
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2025-06-01
Series:eLife
Subjects:
self-supervised learning
artificial intelligence
neuroscience
mesoSPIM
confocal microscopy
platynereis
Online Access:https://elifesciences.org/articles/99848
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https://elifesciences.org/articles/99848

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