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K2S Challenge: From Undersampled K-Space to Automatic Segmentation

K2S Challenge: From Undersampled K-Space to Automatic Segmentation

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_1575c91d76ad4fca8925da8dfeb594a6

K2S Challenge: From Undersampled K-Space to Automatic Segmentation

Publication information

Publisher

Switzerland: MDPI AG

More information

Scope and Contents

Contents

Magnetic Resonance Imaging (MRI) offers strong soft tissue contrast but suffers from long acquisition times and requires tedious annotation from radiologists. Traditionally, these challenges have been addressed separately with reconstruction and image analysis algorithms. To see if performance could be improved by treating both as end-to-end, we ho...

Alternative Titles

Full title

K2S Challenge: From Undersampled K-Space to Automatic Segmentation

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_1575c91d76ad4fca8925da8dfeb594a6

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_1575c91d76ad4fca8925da8dfeb594a6

Other Identifiers

ISSN

2306-5354

E-ISSN

2306-5354

DOI

10.3390/bioengineering10020267

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