View in EDS

Using multimodal PET+MR data as conditional generative adversarial network inputs improves pseudo-CT and attenuation correction estimates for brain PET/MR.

Saved in:
Bibliographic Details
Title: Using multimodal PET+MR data as conditional generative adversarial network inputs improves pseudo-CT and attenuation correction estimates for brain PET/MR.
Authors: Fisher J; Department of Electrical Engineering, Stanford University Stanford, CA, USA.; Department of Radiology, Stanford University Stanford, CA, USA., Anaya E; Department of Electrical Engineering, Stanford University Stanford, CA, USA.; Department of Radiology, Stanford University Stanford, CA, USA., Chinn G; Department of Radiology, Stanford University Stanford, CA, USA., Levin CS; Department of Electrical Engineering, Stanford University Stanford, CA, USA.; Department of Radiology, Stanford University Stanford, CA, USA.; Department of Physics, Stanford University Stanford, CA, USA.; Department of Bioengineering, Stanford University Stanford, CA, USA.
Source: American journal of nuclear medicine and molecular imaging [Am J Nucl Med Mol Imaging] 2026 Feb 15; Vol. 16 (1), pp. 44-54. Date of Electronic Publication: 2026 Feb 15 (Print Publication: 2026).
Publication Type: Journal Article
Journal Info: Publisher: e-Century Pub. Corp Country of Publication: United States NLM ID: 101564121 Publication Model: eCollection Cited Medium: Print ISSN: 2160-8407 (Print) NLM ISO Abbreviation: Am J Nucl Med Mol Imaging Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
FullText Text:
  Availability: 0
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 41868682
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Using multimodal PET+MR data as conditional generative adversarial network inputs improves pseudo-CT and attenuation correction estimates for brain PET/MR.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Fisher+J%22">Fisher J</searchLink>; Department of Electrical Engineering, Stanford University Stanford, CA, USA.; Department of Radiology, Stanford University Stanford, CA, USA.<br /><searchLink fieldCode="AU" term="%22Anaya+E%22">Anaya E</searchLink>; Department of Electrical Engineering, Stanford University Stanford, CA, USA.; Department of Radiology, Stanford University Stanford, CA, USA.<br /><searchLink fieldCode="AU" term="%22Chinn+G%22">Chinn G</searchLink>; Department of Radiology, Stanford University Stanford, CA, USA.<br /><searchLink fieldCode="AU" term="%22Levin+CS%22">Levin CS</searchLink>; Department of Electrical Engineering, Stanford University Stanford, CA, USA.; Department of Radiology, Stanford University Stanford, CA, USA.; Department of Physics, Stanford University Stanford, CA, USA.; Department of Bioengineering, Stanford University Stanford, CA, USA.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22101564121%22">American journal of nuclear medicine and molecular imaging</searchLink> [Am J Nucl Med Mol Imaging] 2026 Feb 15; Vol. 16 (1), pp. 44-54. <i>Date of Electronic Publication: </i>2026 Feb 15 (<i>Print Publication: </i>2026).
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Journal Article
– Name: TitleSource
  Label: Journal Info
  Group: Src
  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22e-Century+Pub%2E+Corp%22">e-Century Pub. Corp </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101564121 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Print <i>ISSN: </i>2160-8407 (Print) <i>NLM ISO Abbreviation: </i>Am J Nucl Med Mol Imaging <i>Subsets: </i>PubMed not MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41868682
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.62347/BONK5634
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 44
    Titles:
      – TitleFull: Using multimodal PET+MR data as conditional generative adversarial network inputs improves pseudo-CT and attenuation correction estimates for brain PET/MR.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Fisher J
      – PersonEntity:
          Name:
            NameFull: Anaya E
      – PersonEntity:
          Name:
            NameFull: Chinn G
      – PersonEntity:
          Name:
            NameFull: Levin CS
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 02
              Text: 2026 Feb 15
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 2160-8407
          Numbering:
            – Type: volume
              Value: 16
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: American journal of nuclear medicine and molecular imaging
              Type: main
ResultId 1