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Autoencoder-Inspired Convolutional Network-Based Super-Resolution Method in MRI.

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Title: Autoencoder-Inspired Convolutional Network-Based Super-Resolution Method in MRI.
Authors: Park S; Department of BioengineeringUniversity of Illinois at Urbana-Champaign Urbana IL 61820 USA., Gach HM; Department of Radiation OncologyWashington University in St. Louis St. Louis MO 63130 USA., Kim S; Department of Radiation OncologyDivision of Medical PhysicsVirginia Commonwealth University Richmond VA 23284 USA., Lee SJ; TSYS School of Computer ScienceColumbus State University Columbus GA 31907 USA., Motai Y; Department of Electrical and Computer EngineeringVirginia Commonwealth University Richmond VA 23284 USA.
Source: IEEE journal of translational engineering in health and medicine [IEEE J Transl Eng Health Med] 2021 Apr 28; Vol. 9, pp. 1800113. Date of Electronic Publication: 2021 Apr 28 (Print Publication: 2021).
Publication Type: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Institute of Electrical and Electronics Engineers Country of Publication: United States NLM ID: 101623153 Publication Model: eCollection Cited Medium: Internet ISSN: 2168-2372 (Electronic) Linking ISSN: 21682372 NLM ISO Abbreviation: IEEE J Transl Eng Health Med Subsets: MEDLINE
Database: MEDLINE Ultimate
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PubType: Academic Journal
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  Data: <searchLink fieldCode="AU" term="%22Park+S%22">Park S</searchLink>; Department of BioengineeringUniversity of Illinois at Urbana-Champaign Urbana IL 61820 USA.<br /><searchLink fieldCode="AU" term="%22Gach+HM%22">Gach HM</searchLink>; Department of Radiation OncologyWashington University in St. Louis St. Louis MO 63130 USA.<br /><searchLink fieldCode="AU" term="%22Kim+S%22">Kim S</searchLink>; Department of Radiation OncologyDivision of Medical PhysicsVirginia Commonwealth University Richmond VA 23284 USA.<br /><searchLink fieldCode="AU" term="%22Lee+SJ%22">Lee SJ</searchLink>; TSYS School of Computer ScienceColumbus State University Columbus GA 31907 USA.<br /><searchLink fieldCode="AU" term="%22Motai+Y%22">Motai Y</searchLink>; Department of Electrical and Computer EngineeringVirginia Commonwealth University Richmond VA 23284 USA.
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  Data: <searchLink fieldCode="JN" term="%22101623153%22">IEEE journal of translational engineering in health and medicine</searchLink> [IEEE J Transl Eng Health Med] 2021 Apr 28; Vol. 9, pp. 1800113. <i>Date of Electronic Publication: </i>2021 Apr 28 (<i>Print Publication: </i>2021).
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Institute+of+Electrical+and+Electronics+Engineers%22">Institute of Electrical and Electronics Engineers </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101623153 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Internet <i>ISSN: </i>2168-2372 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2221682372%22">21682372 </searchLink><i>NLM ISO Abbreviation: </i>IEEE J Transl Eng Health Med <i>Subsets: </i>MEDLINE
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      – Type: doi
        Value: 10.1109/JTEHM.2021.3076152
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      – Code: eng
        Text: English
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        StartPage: 1800113
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      – TitleFull: Autoencoder-Inspired Convolutional Network-Based Super-Resolution Method in MRI.
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            NameFull: Park S
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            NameFull: Gach HM
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            NameFull: Kim S
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            – D: 28
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              Text: 2021 Apr 28
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