PURPOSE: Numerical simulations studying the interactions between radiations and biological tissues require the use of three-dimensional models of the human anatomy at various ages and in various positions. Several detailed and flexible models exist for adults and children and have been extensively used for dosimetry. On the other hand, progress of simulation studies focusing on pregnant women and the fetus have been limited by the fact that only a small number of models exist with rather coarse anatomical details and a poor representation of the anatomical variability of the fetus shape and its position over the entire gestation. METHODS: In this paper, we propose a new computational framework to generate 3D hybrid models of pregnant women, composed of fetus shapes segmented from medical images and a generic maternal body envelope representing a synthetic woman scaled to the dimension of the uterus. The computational framework includes the following tasks: image segmentation, contour regularization, mesh-based surface reconstruction, and model integration. RESULTS: A series of models was created to represent pregnant women at different gestational stages and with the fetus in different positions, all including detailed tissues of the fetus and the utero-fetal unit, which play an important role in dosimetry. These models were anatomically validated by clinical obstetricians and radiologists who verified the accuracy and representativeness of the anatomical details, and the positioning of the fetus inside the maternal body. CONCLUSION: The computational framework enables the creation of detailed, realistic, and representative fetus models from medical images, directly exploitable for dosimetry simulations.
PURPOSE: Numerical simulations studying the interactions between radiations and biological tissues require the use of three-dimensional models of the human anatomy at various ages and in various positions. Several detailed and flexible models exist for adults and children and have been extensively used for dosimetry. On the other hand, progress of simulation studies focusing on pregnant women and the fetus have been limited by the fact that only a small number of models exist with rather coarse anatomical details and a poor representation of the anatomical variability of the fetus shape and its position over the entire gestation. METHODS: In this paper, we propose a new computational framework to generate 3D hybrid models of pregnant women, composed of fetus shapes segmented from medical images and a generic maternal body envelope representing a synthetic woman scaled to the dimension of the uterus. The computational framework includes the following tasks: image segmentation, contour regularization, mesh-based surface reconstruction, and model integration. RESULTS: A series of models was created to represent pregnant women at different gestational stages and with the fetus in different positions, all including detailed tissues of the fetus and the utero-fetal unit, which play an important role in dosimetry. These models were anatomically validated by clinical obstetricians and radiologists who verified the accuracy and representativeness of the anatomical details, and the positioning of the fetus inside the maternal body. CONCLUSION: The computational framework enables the creation of detailed, realistic, and representative fetus models from medical images, directly exploitable for dosimetry simulations.