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A two-step deep learning method for 3DCT-2DUS kidney registration during breathing

A two-step deep learning method for 3DCT-2DUS kidney registration during breathing

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_a731d7e30cff44ce864b8864b9290882

A two-step deep learning method for 3DCT-2DUS kidney registration during breathing

About this item

Full title

A two-step deep learning method for 3DCT-2DUS kidney registration during breathing

Publisher

London: Nature Publishing Group UK

Journal title

Scientific reports, 2023-08, Vol.13 (1), p.12846-12846, Article 12846

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

This work proposed KidneyRegNet, a novel deep registration pipeline for 3D CT and 2D U/S kidney scans of free breathing, which comprises a feature network, and a 3D–2D CNN-based registration network. The feature network has handcrafted texture feature layers to reduce the semantic gap. The registration network is an encoder-decoder structure with l...

Alternative Titles

Full title

A two-step deep learning method for 3DCT-2DUS kidney registration during breathing

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_a731d7e30cff44ce864b8864b9290882

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_a731d7e30cff44ce864b8864b9290882

Other Identifiers

ISSN

2045-2322

E-ISSN

2045-2322

DOI

10.1038/s41598-023-40133-5

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