Deformable motion compensation in interventional cone-beam CT with a context-aware learned autofocus metric.
deep autofocus
deformable motion
interventional CBCT
Journal
Medical physics
ISSN: 2473-4209
Titre abrégé: Med Phys
Pays: United States
ID NLM: 0425746
Informations de publication
Date de publication:
11 May 2024
11 May 2024
Historique:
revised:
02
04
2024
received:
25
12
2023
accepted:
03
05
2024
medline:
11
5
2024
pubmed:
11
5
2024
entrez:
11
5
2024
Statut:
aheadofprint
Résumé
Interventional Cone-Beam CT (CBCT) offers 3D visualization of soft-tissue and vascular anatomy, enabling 3D guidance of abdominal interventions. However, its long acquisition time makes CBCT susceptible to patient motion. Image-based autofocus offers a suitable platform for compensation of deformable motion in CBCT, but it relies on handcrafted motion metrics based on first-order image properties and that lack awareness of the underlying anatomy. This work proposes a data-driven approach to motion quantification via a learned, context-aware, deformable metric, The proposed The magnitude and spatial map of The proposed
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : NIBIB NIH HHS
ID : R01EB030547
Pays : United States
Informations de copyright
© 2024 American Association of Physicists in Medicine.
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