Artificial intelligence to generate synthetic CT for adaptive particle therapy
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Author (Corporation)
Publication date
06/2024
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Type
04A - Book part
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Parent work
Imaging in particle therapy. Current practice and future trends
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DOI of the original publication
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Issue / Number
Pages / Duration
8-16
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Publisher / Publishing institution
IOP Publishing
Place of publication / Event location
Bristol
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Abstract
Recently, Artificial Intelligence (AI) methods for the generation of synthetic computed tomography (sCT) have received significant research attention as an alternative to classical ones (e.g. bulk density assignment, atlas based virtual CT). We present here an overview of these methods for particle therapy (PT) applications, including strategies to replace CT in magnetic resonance imaging (MRI)-based treatment planning and to facilitate cone beam CT (CBCT)-based image-guided adaptive PT.
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ISBN
978-0-7503-5117-1
978-0-7503-5115-7
978-0-7503-5115-7
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Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
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Peer review of the complete publication
Open access category
Closed
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Citation
Thummerer, A., Zaffino, P., Spadea, M. F., Knopf, A., & Maspero, M. (2024). Artificial intelligence to generate synthetic CT for adaptive particle therapy. In C. Paganelli, C. Gianoli, & A. Knopf (Eds.), Imaging in particle therapy. Current practice and future trends (pp. 8–16). IOP Publishing. https://doi.org/10.1088/978-0-7503-5117-1ch8