Reduction of Gadolinium-Based Contrast Agents in MRI Using Convolutional Neural Networks and Different Input Protocols: Limited Interchangeability of Synthesized Sequences With Original Full-Dose Images Despite Excellent Quantitative Performance.
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| Title: | Reduction of Gadolinium-Based Contrast Agents in MRI Using Convolutional Neural Networks and Different Input Protocols: Limited Interchangeability of Synthesized Sequences With Original Full-Dose Images Despite Excellent Quantitative Performance. |
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| Authors: | Haase R, Pinetz T; Institute of Applied Mathematics, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany., Bendella Z; From the Department of Neuroradiology, University Medical Center Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn., Kobler E; From the Department of Neuroradiology, University Medical Center Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn., Paech D, Block W; From the Department of Neuroradiology, University Medical Center Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn., Effland A; Institute of Applied Mathematics, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany., Radbruch A, Deike-Hofmann K |
| Source: | Investigative radiology [Invest Radiol] 2023 Jun 01; Vol. 58 (6), pp. 420-430. Date of Electronic Publication: 2023 Jan 28. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 0045377 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1536-0210 (Electronic) Linking ISSN: 00209996 NLM ISO Abbreviation: Invest Radiol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 36735399 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Reduction of Gadolinium-Based Contrast Agents in MRI Using Convolutional Neural Networks and Different Input Protocols: Limited Interchangeability of Synthesized Sequences With Original Full-Dose Images Despite Excellent Quantitative Performance. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Haase+R%22">Haase R</searchLink><br /><searchLink fieldCode="AU" term="%22Pinetz+T%22">Pinetz T</searchLink>; Institute of Applied Mathematics, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany.<br /><searchLink fieldCode="AU" term="%22Bendella+Z%22">Bendella Z</searchLink>; From the Department of Neuroradiology, University Medical Center Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn.<br /><searchLink fieldCode="AU" term="%22Kobler+E%22">Kobler E</searchLink>; From the Department of Neuroradiology, University Medical Center Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn.<br /><searchLink fieldCode="AU" term="%22Paech+D%22">Paech D</searchLink><br /><searchLink fieldCode="AU" term="%22Block+W%22">Block W</searchLink>; From the Department of Neuroradiology, University Medical Center Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn.<br /><searchLink fieldCode="AU" term="%22Effland+A%22">Effland A</searchLink>; Institute of Applied Mathematics, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany.<br /><searchLink fieldCode="AU" term="%22Radbruch+A%22">Radbruch A</searchLink><br /><searchLink fieldCode="AU" term="%22Deike-Hofmann+K%22">Deike-Hofmann K</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%220045377%22">Investigative radiology</searchLink> [Invest Radiol] 2023 Jun 01; Vol. 58 (6), pp. 420-430. <i>Date of Electronic Publication: </i>2023 Jan 28. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article; Research Support, Non-U.S. Gov't – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Lippincott+Williams+%26+Wilkins%22">Lippincott Williams & Wilkins </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>0045377 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1536-0210 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2200209996%22">00209996 </searchLink><i>NLM ISO Abbreviation: </i>Invest Radiol <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=36735399 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1097/RLI.0000000000000955 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 420 Titles: – TitleFull: Reduction of Gadolinium-Based Contrast Agents in MRI Using Convolutional Neural Networks and Different Input Protocols: Limited Interchangeability of Synthesized Sequences With Original Full-Dose Images Despite Excellent Quantitative Performance. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Haase R – PersonEntity: Name: NameFull: Pinetz T – PersonEntity: Name: NameFull: Bendella Z – PersonEntity: Name: NameFull: Kobler E – PersonEntity: Name: NameFull: Paech D – PersonEntity: Name: NameFull: Block W – PersonEntity: Name: NameFull: Effland A – PersonEntity: Name: NameFull: Radbruch A – PersonEntity: Name: NameFull: Deike-Hofmann K IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: 2023 Jun 01 Type: published Y: 2023 Identifiers: – Type: issn-electronic Value: 1536-0210 Numbering: – Type: volume Value: 58 – Type: issue Value: 6 Titles: – TitleFull: Investigative radiology Type: main |
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