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Machine learning for the prediction of pseudorealistic pediatric abdominal phantoms for radiation dose reconstruction

Purpose: Current phantoms used for the dose reconstruction of long-term childhood cancer survivors lack individualization. We design a method to predict highly individualized abdominal three-dimensional (3-D) phantoms automatically. Approach: We train machine learning (ML) models to map (2-D) patien...

Täydet tiedot

Tallennettuna:
Bibliografiset tiedot
Julkaisussa:J Med Imaging (Bellingham)
Päätekijät: Virgolin, Marco, Wang, Ziyuan, Alderliesten, Tanja, Bosman, Peter A. N.
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: Society of Photo-Optical Instrumentation Engineers 2020
Aiheet:
Linkit:https://ncbi.nlm.nih.gov/pmc/articles/PMC7390892/
https://ncbi.nlm.nih.gov/pubmed/32743017
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/1.JMI.7.4.046501
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