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FDE-net: Frequency-domain enhancement network using dynamic-scale dilated convolution for thyroid no...

FDE-net: Frequency-domain enhancement network using dynamic-scale dilated convolution for thyroid no...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2764444116

FDE-net: Frequency-domain enhancement network using dynamic-scale dilated convolution for thyroid nodule segmentation

About this item

Full title

FDE-net: Frequency-domain enhancement network using dynamic-scale dilated convolution for thyroid nodule segmentation

Publisher

United States: Elsevier Ltd

Journal title

Computers in biology and medicine, 2023-02, Vol.153, p.106514-106514, Article 106514

Language

English

Formats

Publication information

Publisher

United States: Elsevier Ltd

More information

Scope and Contents

Contents

AbstractThyroid nodules, a common disease of endocrine system, have a probability of nearly 10% to turn into malignant nodules and thus pose a serious threat to health. Automatic segmentation of thyroid nodules is of great importance for clinicopathological diagnosis. This work proposes FDE-Net, a combined segmental frequency domain enhancement and...

Alternative Titles

Full title

FDE-net: Frequency-domain enhancement network using dynamic-scale dilated convolution for thyroid nodule segmentation

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_miscellaneous_2764444116

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2764444116

Other Identifiers

ISSN

0010-4825

E-ISSN

1879-0534

DOI

10.1016/j.compbiomed.2022.106514

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