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Validation of Fully-Automated Deep Learning-Based Fibroglandular Tissue Segmentation for Efficient and Reliable Quantitation of Background Parenchymal Enhancement in Breast MRI.

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Title: Validation of Fully-Automated Deep Learning-Based Fibroglandular Tissue Segmentation for Efficient and Reliable Quantitation of Background Parenchymal Enhancement in Breast MRI.
Authors: Kuo YT, Kazerouni AS, Park VY, Surento W, Sujichantararat S, Hippe DS, Rahbar H, Partridge SC
Source: ArXiv [ArXiv] 2025 Nov 10. Date of Electronic Publication: 2025 Nov 10.
Publication Type: Journal Article; Preprint
Journal Info: Country of Publication: United States NLM ID: 101759493 Publication Model: Electronic Cited Medium: Internet ISSN: 2331-8422 (Electronic) Linking ISSN: 23318422 NLM ISO Abbreviation: ArXiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Availability: 0
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 41293527
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Validation of Fully-Automated Deep Learning-Based Fibroglandular Tissue Segmentation for Efficient and Reliable Quantitation of Background Parenchymal Enhancement in Breast MRI.
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  Data: <searchLink fieldCode="AU" term="%22Kuo+YT%22">Kuo YT</searchLink><br /><searchLink fieldCode="AU" term="%22Kazerouni+AS%22">Kazerouni AS</searchLink><br /><searchLink fieldCode="AU" term="%22Park+VY%22">Park VY</searchLink><br /><searchLink fieldCode="AU" term="%22Surento+W%22">Surento W</searchLink><br /><searchLink fieldCode="AU" term="%22Sujichantararat+S%22">Sujichantararat S</searchLink><br /><searchLink fieldCode="AU" term="%22Hippe+DS%22">Hippe DS</searchLink><br /><searchLink fieldCode="AU" term="%22Rahbar+H%22">Rahbar H</searchLink><br /><searchLink fieldCode="AU" term="%22Partridge+SC%22">Partridge SC</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22101759493%22">ArXiv</searchLink> [ArXiv] 2025 Nov 10. <i>Date of Electronic Publication: </i>2025 Nov 10.
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  Data: <i>Country of Publication: </i>United States <i>NLM ID: </i>101759493 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2331-8422 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2223318422%22">23318422 </searchLink><i>NLM ISO Abbreviation: </i>ArXiv <i>Subsets: </i>PubMed not MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41293527
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    Languages:
      – Code: eng
        Text: English
    Titles:
      – TitleFull: Validation of Fully-Automated Deep Learning-Based Fibroglandular Tissue Segmentation for Efficient and Reliable Quantitation of Background Parenchymal Enhancement in Breast MRI.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Kuo YT
      – PersonEntity:
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            NameFull: Kazerouni AS
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            NameFull: Park VY
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            NameFull: Surento W
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            NameFull: Sujichantararat S
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            NameFull: Hippe DS
      – PersonEntity:
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            NameFull: Rahbar H
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            NameFull: Partridge SC
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          Dates:
            – D: 10
              M: 11
              Text: 2025 Nov 10
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-electronic
              Value: 2331-8422
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