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Deep learning-enabled segmentation of ambiguous bioimages with deepflash2

Deep learning-enabled segmentation of ambiguous bioimages with deepflash2

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_7de380a95c5a4512844457ad18074389

Deep learning-enabled segmentation of ambiguous bioimages with deepflash2

About this item

Full title

Deep learning-enabled segmentation of ambiguous bioimages with deepflash2

Publisher

London: Nature Publishing Group UK

Journal title

Nature communications, 2023-03, Vol.14 (1), p.1679-1679, Article 1679

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

Bioimages frequently exhibit low signal-to-noise ratios due to experimental conditions, specimen characteristics, and imaging trade-offs. Reliable segmentation of such ambiguous images is difficult and laborious. Here we introduce deepflash2, a deep learning-enabled segmentation tool for bioimage analysis. The tool addresses typical challenges that...

Alternative Titles

Full title

Deep learning-enabled segmentation of ambiguous bioimages with deepflash2

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_7de380a95c5a4512844457ad18074389

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_7de380a95c5a4512844457ad18074389

Other Identifiers

ISSN

2041-1723

E-ISSN

2041-1723

DOI

10.1038/s41467-023-36960-9

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