3D printed phantom with 12 000 submillimeter lesions to improve efficiency in CT detectability assessment.
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| Title: | 3D printed phantom with 12 000 submillimeter lesions to improve efficiency in CT detectability assessment. |
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| Authors: | Shunhavanich P; Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA., Mei K; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA., Shapira N; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA., Stayman JW; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA., McCollough CH; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA., Gang G; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA., Leng S; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA., Geagan M; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA., Yu L; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA., Noël PB; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA., Hsieh SS; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA. |
| Source: | Medical physics [Med Phys] 2024 May; Vol. 51 (5), pp. 3265-3274. Date of Electronic Publication: 2024 Apr 08. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: John Wiley and Sons, Inc Country of Publication: United States NLM ID: 0425746 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2473-4209 (Electronic) Linking ISSN: 00942405 NLM ISO Abbreviation: Med Phys Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 38588491 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: 3D printed phantom with 12 000 submillimeter lesions to improve efficiency in CT detectability assessment. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Shunhavanich+P%22">Shunhavanich P</searchLink>; Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA.<br /><searchLink fieldCode="AU" term="%22Mei+K%22">Mei K</searchLink>; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.<br /><searchLink fieldCode="AU" term="%22Shapira+N%22">Shapira N</searchLink>; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.<br /><searchLink fieldCode="AU" term="%22Stayman+JW%22">Stayman JW</searchLink>; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.<br /><searchLink fieldCode="AU" term="%22McCollough+CH%22">McCollough CH</searchLink>; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA.<br /><searchLink fieldCode="AU" term="%22Gang+G%22">Gang G</searchLink>; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.<br /><searchLink fieldCode="AU" term="%22Leng+S%22">Leng S</searchLink>; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA.<br /><searchLink fieldCode="AU" term="%22Geagan+M%22">Geagan M</searchLink>; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.<br /><searchLink fieldCode="AU" term="%22Yu+L%22">Yu L</searchLink>; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA.<br /><searchLink fieldCode="AU" term="%22Noël+PB%22">Noël PB</searchLink>; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.<br /><searchLink fieldCode="AU" term="%22Hsieh+SS%22">Hsieh SS</searchLink>; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%220425746%22">Medical physics</searchLink> [Med Phys] 2024 May; Vol. 51 (5), pp. 3265-3274. <i>Date of Electronic Publication: </i>2024 Apr 08. – 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="%22John+Wiley+and+Sons%2C+Inc%22">John Wiley and Sons, Inc </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>0425746 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2473-4209 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2200942405%22">00942405 </searchLink><i>NLM ISO Abbreviation: </i>Med Phys <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=38588491 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/mp.17064 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 3265 Titles: – TitleFull: 3D printed phantom with 12 000 submillimeter lesions to improve efficiency in CT detectability assessment. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Shunhavanich P – PersonEntity: Name: NameFull: Mei K – PersonEntity: Name: NameFull: Shapira N – PersonEntity: Name: NameFull: Stayman JW – PersonEntity: Name: NameFull: McCollough CH – PersonEntity: Name: NameFull: Gang G – PersonEntity: Name: NameFull: Leng S – PersonEntity: Name: NameFull: Geagan M – PersonEntity: Name: NameFull: Yu L – PersonEntity: Name: NameFull: Noël PB – PersonEntity: Name: NameFull: Hsieh SS IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: 2024 May Type: published Y: 2024 Identifiers: – Type: issn-electronic Value: 2473-4209 Numbering: – Type: volume Value: 51 – Type: issue Value: 5 Titles: – TitleFull: Medical physics Type: main |
| ResultId | 1 |