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A deep convolutional neural network-based automatic delineation strategy for multiple brain metastas...

A deep convolutional neural network-based automatic delineation strategy for multiple brain metastas...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_1947851456

A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery

About this item

Full title

A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery

Publisher

United States: Public Library of Science

Journal title

PloS one, 2017-10, Vol.12 (10), p.e0185844-e0185844

Language

English

Formats

Publication information

Publisher

United States: Public Library of Science

More information

Scope and Contents

Contents

Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS) treatment planning. In this work, we developed a deep learning convolutional neural network (CNN) algorithm for segmenting brain metastases on contrast-enhanced T1-weighted magnetic resonance imaging (MRI) datasets. W...

Alternative Titles

Full title

A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_plos_journals_1947851456

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_1947851456

Other Identifiers

ISSN

1932-6203

E-ISSN

1932-6203

DOI

10.1371/journal.pone.0185844

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