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Abstract No. 197 ▪ FEATURED ABSTRACT Feasibility of Deep Le..:
Lee, A.
;
Ahna, C.
;
bae, y.
..
Journal of Vascular and Interventional Radiology. 35 (2024) 3 - p. S88-S89 , 2024
Link:
https://doi.org/10.1016/j.jvir.2023.12.236
RT Journal T1 <Title>Abstract No. 197 ▪ FEATURED ABSTRACT Feasibility of Deep Learning-enabled Quarter Dose Interventional Cone-Beam CT: Image Quality Evaluation</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1016_j.jvir.2023.12.236&Exemplar=1&LAN=DE A1 Lee, A. A1 Ahna, C. A1 bae, y. A1 Hur, S. A1 kim, j. PB Elsevier BV YR 2024 SN 1051-0443 JF Journal of Vascular and Interventional Radiology VO 35 IS 3 SP S88 OP S89 LK http://dx.doi.org/https://doi.org/10.1016/j.jvir.2023.12.236 DO https://doi.org/10.1016/j.jvir.2023.12.236 SF ELIB - SuUB Bremen
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