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

Objectives 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 ba...

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Veröffentlicht in:	European radiology Jg. 29; H. 12; S. 6805 - 6815
Hauptverfasser:	Xie, Tianwu, Zaidi, Habib
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2019 Springer Nature B.V
Schlagworte:	Adult Algorithms Artificial neural networks Automation Computation Computed tomography Computer applications Computer Simulation Construction Decision making Diagnostic Radiology Diagnostic systems Dosimetry Embryos Female Fetuses Hazards Humans Image processing Image segmentation Imaging Internal Medicine Interventional Radiology Lungs Mathematical models Medical imaging Medicine Medicine & Public Health Methodology Metric space Middle Aged Monte Carlo Method Neural networks Neural Networks, Computer Neuroradiology Nuclear medicine Organs Phantoms, Imaging Physics Pregnancy Radiation Radiation Dosage Radiation hazards Radiography, Abdominal - methods Radiography, Abdominal - statistics & numerical data Radiology Radiometry - methods Radiosensitivity Risk analysis Risk assessment Tomography, X-Ray Computed - methods Tomography, X-Ray Computed - statistics & numerical data Ultrasound Uterus Young Adult Radiation dosimetry Multidetector-row computed tomography Radiologic phantoms Patient-specific computational modeling
ISSN:	0938-7994, 1432-1084, 1432-1084
Online-Zugang:	Volltext
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