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Voxel-wise deep learning segmentation of hydroxyapatite and iodine in spectral photon-counting CT: A quantitative phantom study

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Published in:PLOS ONE
Format: Online Article RSS Article
Published: 2026
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discipline_display Engineering & Technology
discipline_facet Engineering & Technology
format Online Article
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institution FRELIP
journal_source_facet PLOS ONE
publishDate 2026
publishDateSort 2026
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spellingShingle Voxel-wise deep learning segmentation of hydroxyapatite and iodine in spectral photon-counting CT: A quantitative phantom study
Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
sub_discipline_display Computer Science & IT
sub_discipline_facet Computer Science & IT
subject_display Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
subject_facet Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
title Voxel-wise deep learning segmentation of hydroxyapatite and iodine in spectral photon-counting CT: A quantitative phantom study
title_auth Voxel-wise deep learning segmentation of hydroxyapatite and iodine in spectral photon-counting CT: A quantitative phantom study
title_full Voxel-wise deep learning segmentation of hydroxyapatite and iodine in spectral photon-counting CT: A quantitative phantom study
title_fullStr Voxel-wise deep learning segmentation of hydroxyapatite and iodine in spectral photon-counting CT: A quantitative phantom study
title_full_unstemmed Voxel-wise deep learning segmentation of hydroxyapatite and iodine in spectral photon-counting CT: A quantitative phantom study
title_short Voxel-wise deep learning segmentation of hydroxyapatite and iodine in spectral photon-counting CT: A quantitative phantom study
title_sort voxel-wise deep learning segmentation of hydroxyapatite and iodine in spectral photon-counting ct: a quantitative phantom study
topic Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
url https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0346825