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Self-Supervised Joint Learning for pCLE Image Denoising

Self-Supervised Joint Learning for pCLE Image Denoising

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6073af442b2842a8874d105b405f36fb

Self-Supervised Joint Learning for pCLE Image Denoising

About this item

Full title

Self-Supervised Joint Learning for pCLE Image Denoising

Publisher

Switzerland: MDPI AG

Journal title

Sensors (Basel, Switzerland), 2024-05, Vol.24 (9), p.2853

Language

English

Formats

Publication information

Publisher

Switzerland: MDPI AG

More information

Scope and Contents

Contents

Probe-based confocal laser endoscopy (pCLE) has emerged as a powerful tool for disease diagnosis, yet it faces challenges such as the formation of hexagonal patterns in images due to the inherent characteristics of fiber bundles. Recent advancements in deep learning offer promise in image denoising, but the acquisition of clean-noisy image pairs fo...

Alternative Titles

Full title

Self-Supervised Joint Learning for pCLE Image Denoising

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_6073af442b2842a8874d105b405f36fb

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6073af442b2842a8874d105b405f36fb

Other Identifiers

ISSN

1424-8220

E-ISSN

1424-8220

DOI

10.3390/s24092853

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