MR Imaging–based Multimodal Autoidentification of Perivascular Spaces (mMAPS): Automated Morphologic Segmentation of Enlarged Perivascular Spaces at Clinical Field Strength

PURPOSE: To describe a fully automated segmentation method that yields object-based morphologic estimates of enlarged perivascular spaces (ePVSs) in clinical-field-strength (3.0-T) magnetic resonance (MR) imaging data. MATERIALS AND METHODS: In this HIPAA-compliant study, MR imaging data were obtain...

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Bibliografski detalji
Izdano u:Radiology
Glavni autori: Boespflug, Erin L., Schwartz, Daniel L., Lahna, David, Pollock, Jeffrey, Iliff, Jeffrey J., Kaye, Jeffrey A., Rooney, William, Silbert, Lisa C.
Format: Artigo
Jezik:Inglês
Izdano: Radiological Society of North America 2018
Teme:
Original Research
Online pristup:https://ncbi.nlm.nih.gov/pmc/articles/PMC5790307/
https://ncbi.nlm.nih.gov/pubmed/28853674
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1148/radiol.2017170205
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