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Kidney segmentation from DCE-MRI converging level set methods, fuzzy clustering and Markov random fi...

Kidney segmentation from DCE-MRI converging level set methods, fuzzy clustering and Markov random fi...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_bd628a00d84c4bdfaba2a601ed543f91

Kidney segmentation from DCE-MRI converging level set methods, fuzzy clustering and Markov random field modeling

About this item

Full title

Kidney segmentation from DCE-MRI converging level set methods, fuzzy clustering and Markov random field modeling

Publisher

London: Nature Publishing Group UK

Journal title

Scientific reports, 2022-11, Vol.12 (1), p.18816-18816, Article 18816

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

Early diagnosis of transplanted kidney function requires precise Kidney segmentation from Dynamic Contrast-Enhanced Magnetic Resonance Imaging images as a preliminary step. In this regard, this paper aims to propose an automated and accurate DCE-MRI kidney segmentation method integrating fuzzy c-means (FCM) clustering and Markov random field modeli...

Alternative Titles

Full title

Kidney segmentation from DCE-MRI converging level set methods, fuzzy clustering and Markov random field modeling

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_bd628a00d84c4bdfaba2a601ed543f91

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_bd628a00d84c4bdfaba2a601ed543f91

Other Identifiers

ISSN

2045-2322

E-ISSN

2045-2322

DOI

10.1038/s41598-022-23408-1

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