Identification of CT radiomic features robust to acquisition and segmentation variations for improved prediction of radiotherapy-treated lung cancer patient recurrence.
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| Title: | Identification of CT radiomic features robust to acquisition and segmentation variations for improved prediction of radiotherapy-treated lung cancer patient recurrence. |
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| Authors: | Louis, Thomas1 (AUTHOR) Thomas.louis@chuliege.be, Lucia, François1,2,3 (AUTHOR) francois.lucia@chu-brest.fr, Cousin, François1 (AUTHOR), Mievis, Carole4 (AUTHOR), Jansen, Nicolas4 (AUTHOR), Duysinx, Bernard5 (AUTHOR), Le Pennec, Romain6,7 (AUTHOR), Visvikis, Dimitris3 (AUTHOR), Nebbache, Malik2 (AUTHOR), Rehn, Martin2 (AUTHOR), Hamya, Mohamed2 (AUTHOR), Geier, Margaux8 (AUTHOR), Salaun, Pierre-Yves6,7 (AUTHOR), Schick, Ulrike2,3 (AUTHOR), Hatt, Mathieu3 (AUTHOR), Coucke, Philippe4 (AUTHOR), Lovinfosse, Pierre1 (AUTHOR), Hustinx, Roland1 (AUTHOR) |
| Source: | Scientific Reports. 4/19/2024, Vol. 14 Issue 1, p1-14. 14p. |
| Database: | Academic Search Ultimate |
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| ISSN: | 20452322 |
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| DOI: | 10.1038/s41598-024-58551-4 |
