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3DCT reconstruction from single X-ray projection using Deep Learning

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Loyen, Estelle [UCL]

The treatment of abdominal or thorax tumor is challenging in particle therapy because the respiratory motion induces a movement of the tumor. One current option to follow the breathing motion is to regularly acquire one (or two) X-ray projection(s) during the treatment, which does not give the full 3D anatomy. The purpose of this work is then to reconstruct a 3DCT image based on a single X-ray projection using a neural network.

Document type Communication à un colloque (Conference Paper) – Présentation orale avec comité de sélection, Abstract
Access type Accès libre
Publication date 2022
Language Anglais
Conference "European Society Radiation Oncology (ESTRO)", Copenhagen (du 06/05/2022 au 10/05/2022)
Journal information "Radiotherapy & Oncology" - Vol. 170, no.1, p. S171-S172 (2022)
Peer reviewed yes
issn 0167-8140
Publication status Publié
Affiliation UCL - SST/ICTM/ELEN - Pôle en ingénierie électrique
Keywords Radiotherapy ; 3D-CT reconstruction
Links
Bibliographic reference Loyen, Estelle ; et. al. 3DCT reconstruction from single X-ray projection using Deep Learning.European Society Radiation Oncology (ESTRO) (Copenhagen, du 06/05/2022 au 10/05/2022). In: Radiotherapy & Oncology, Vol. 170, no.1, p. S171-S172 (2022)
Permanent URL http://hdl.handle.net/2078.1/266042