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Estimation of the radiation dose in pregnancy: an automated patient-specific model using convolutional neural networks

ContributorsXie, Tianwu; Zaidi, Habiborcid
Published inEuropean Radiology, vol. 29, no. 12, p. 6805-6815
Publication date2019
Abstract

The conceptus dose during diagnostic imaging procedures for pregnant patients raises health concerns owing to the high radiosensitivity of the developing embryo/fetus. The aim of this work is to develop a methodology for automated construction of patient-specific computational phantoms based on actual patient CT images to enable accurate estimation of conceptus dose.

Keywords
  • Multidetector-row computed tomography
  • Radiologic phantoms
  • Patient-specific computational modeling
  • Radiation dosimetry
NoteMerci de mettre à jour également le fichier pdf avec:https://www.hug-ge.ch/sites/interhug/files/structures/pinlab/documents/eurradiol2019cnn.pdf
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Citation (ISO format)
XIE, Tianwu, ZAIDI, Habib. Estimation of the radiation dose in pregnancy: an automated patient-specific model using convolutional neural networks. In: European Radiology, 2019, vol. 29, n° 12, p. 6805–6815. doi: 10.1007/s00330-019-06296-4
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accessLevelPublic CC0
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Additional URL for this publicationhttps://www.hug-ge.ch/sites/interhug/files/structures/pinlab/documents/eurradiol2019cnn.pdf
Journal ISSN0938-7994
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Creation24/06/2019 04:01:00
First validation24/06/2019 04:01:00
Update20/01/2025 07:19:07
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