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Self-normalization for a 1 mm3resolution clinical PET system using deep learning.

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Title: Self-normalization for a 1 mm3resolution clinical PET system using deep learning.
Authors: Chin M; Department of Electrical Engineering, Stanford University, Stanford, CA, United States of America.; Department of Radiology, Stanford University, Stanford, CA, United States of America., Jafaritadi M; Department of Radiology, Stanford University, Stanford, CA, United States of America., Franco AB; Department of Mechanical Engineering, Stanford University, Stanford, CA, United States of America., Nasir Ullah M; Department of Radiology, Stanford University, Stanford, CA, United States of America., Chinn G; Department of Radiology, Stanford University, Stanford, CA, United States of America., Innes D; Department of Radiology, Stanford University, Stanford, CA, United States of America., Levin CS; Department of Electrical Engineering, Stanford University, Stanford, CA, United States of America.; Department of Radiology, Stanford University, Stanford, CA, United States of America.; Department of Physics, Stanford University, Stanford, CA, United States of America.; Department of Bioengineering, Stanford University, Stanford, CA, United States of America.
Source: Physics in medicine and biology [Phys Med Biol] 2024 Aug 14; Vol. 69 (17). Date of Electronic Publication: 2024 Aug 14.
Publication Type: Journal Article
Journal Info: Publisher: IOP Publishing Country of Publication: England NLM ID: 0401220 Publication Model: Electronic Cited Medium: Internet ISSN: 1361-6560 (Electronic) Linking ISSN: 00319155 NLM ISO Abbreviation: Phys Med Biol Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Self-normalization for a 1 mm<superscript>3</superscript>resolution clinical PET system using deep learning.
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  Data: <searchLink fieldCode="AU" term="%22Chin+M%22">Chin M</searchLink>; Department of Electrical Engineering, Stanford University, Stanford, CA, United States of America.; Department of Radiology, Stanford University, Stanford, CA, United States of America.<br /><searchLink fieldCode="AU" term="%22Jafaritadi+M%22">Jafaritadi M</searchLink>; Department of Radiology, Stanford University, Stanford, CA, United States of America.<br /><searchLink fieldCode="AU" term="%22Franco+AB%22">Franco AB</searchLink>; Department of Mechanical Engineering, Stanford University, Stanford, CA, United States of America.<br /><searchLink fieldCode="AU" term="%22Nasir+Ullah+M%22">Nasir Ullah M</searchLink>; Department of Radiology, Stanford University, Stanford, CA, United States of America.<br /><searchLink fieldCode="AU" term="%22Chinn+G%22">Chinn G</searchLink>; Department of Radiology, Stanford University, Stanford, CA, United States of America.<br /><searchLink fieldCode="AU" term="%22Innes+D%22">Innes D</searchLink>; Department of Radiology, Stanford University, Stanford, CA, United States of America.<br /><searchLink fieldCode="AU" term="%22Levin+CS%22">Levin CS</searchLink>; Department of Electrical Engineering, Stanford University, Stanford, CA, United States of America.; Department of Radiology, Stanford University, Stanford, CA, United States of America.; Department of Physics, Stanford University, Stanford, CA, United States of America.; Department of Bioengineering, Stanford University, Stanford, CA, United States of America.
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  Data: <searchLink fieldCode="JN" term="%220401220%22">Physics in medicine and biology</searchLink> [Phys Med Biol] 2024 Aug 14; Vol. 69 (17). <i>Date of Electronic Publication: </i>2024 Aug 14.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22IOP+Publishing%22">IOP Publishing </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>0401220 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1361-6560 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2200319155%22">00319155 </searchLink><i>NLM ISO Abbreviation: </i>Phys Med Biol <i>Subsets: </i>MEDLINE
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        Value: 10.1088/1361-6560/ad69fb
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        Text: English
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      – TitleFull: Self-normalization for a 1 mm3resolution clinical PET system using deep learning.
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              Text: 2024 Aug 14
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