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Improving Cerebrovascular Imaging with Deep Learning: Semantic Segmentation for Time-of-Flight Magne...

Improving Cerebrovascular Imaging with Deep Learning: Semantic Segmentation for Time-of-Flight Magne...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3181409427

Improving Cerebrovascular Imaging with Deep Learning: Semantic Segmentation for Time-of-Flight Magnetic Resonance Angiography Maximum Intensity Projection Image Enhancement

About this item

Full title

Improving Cerebrovascular Imaging with Deep Learning: Semantic Segmentation for Time-of-Flight Magnetic Resonance Angiography Maximum Intensity Projection Image Enhancement

Publisher

Basel: MDPI AG

Journal title

Applied sciences, 2025-03, Vol.15 (6), p.3034

Language

English

Formats

Publication information

Publisher

Basel: MDPI AG

More information

Scope and Contents

Contents

Magnetic Resonance Angiography (MRA) is widely used for cerebrovascular assessment, with Time-of-Flight (TOF) MRA being a common non-contrast imaging technique. However, maximum intensity projection (MIP) images generated from TOF-MRA often include non-essential vascular structures such as external carotid branches, requiring manual editing for acc...

Alternative Titles

Full title

Improving Cerebrovascular Imaging with Deep Learning: Semantic Segmentation for Time-of-Flight Magnetic Resonance Angiography Maximum Intensity Projection Image Enhancement

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_journals_3181409427

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3181409427

Other Identifiers

ISSN

2076-3417

E-ISSN

2076-3417

DOI

10.3390/app15063034

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