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AI-Based Longitudinal Scoliosis Monitoring on EOS Whole-Spine Radiographs in a Pediatric to Young Adult Cohort

delete2026-07-07
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OA
AI
J
Julian Enters
A
Adham Zoubi
C
Christian Dascalescu
F
Felix Endres
R
Richard Zaccaria
F
Felix Herr
N
Nina Hesse
B
Boj F. Hoppe
N
Natascha Hohmann
L
Luisa Udoh
M
Maximilian Hamberger
H
Hannah Gildein
V
Verena Schäfer
W
Wegener Bernd
C
Chakravarthy Dussa
C
Christian Ziegler
P
Paul Reidler *
DOI：10.1016/j.acra.2026.06.019delete
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Abstract

Abstract

En 中文
Manual Cobb angle measurement can exhibit high interrater variability, potentially affecting scoliosis management decisions. This study aimed to examine the accuracy of an artificial intelligence (AI) software for automated Cobb angle measurement compared to manual assessments on coronal EOS (EOS Imaging, Paris, France) radiographs of the spine in a pediatric to young adult cohort.
Keywords:
Scoliosis
Artificial intelligence
Radiography
Adolescent
Cobb angle
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Journal

Academic Radiology cover
Academic Radiology
IF:
3.9
Papers:
8.6K
Citations:
1.0W

Organization

U
university hospital munich
Scholars:
20
Papers: 5
Citations: 0
L
lmu university hospital
Scholars:
267
Papers: 71
Citations: 0
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