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Updated: Jan 9, 2026
Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation
Published on: January 7, 2021
Novel multi-level optimization-driven 2D/3D matching for reconstructing 3D fetal postures and motion from childbirth
Tan-Nhu Nguyen1, Morgane Devismes-Ferrandini2, Abbass Ballit3
1School of Biomedical Engineering, International University, Ho Chi Minh City, Vietnam; Vietnam National University, Ho Chi Minh City, Vietnam.
Background And Objective:
The description of 3D fetal postures and movements during vaginal delivery is fundamental for a better understanding of the physiological delivery and the prediction of potential complications and related preventive actions. Recently, 2D dynamic MRI has been developed to characterize in vivo childbirth. However, only 2D information is available. The objective of the present study was to reconstruct the 3D fetal postures and movements from 2D dynamic MRI during vaginal delivery.
Methods:
A multi-level optimization-driven 2D/3D matching procedure was developed and evaluated. Manual segmentation from 2D dynamic MRI was performed. A 3D generic fetal template model was used to match each segmented MRI slice. Fetal postures and associated motion trajectories were extracted and evaluated.
Results:
Consistent results were obtained between the MRI images, segmented slices, and reconstructed 3D fetal postures. A maximum 36.20-degree head-neck extension angle was estimated. A range of torso-neck angles from 1.04 to -16.07 degrees was estimated during the vaginal delivery.
Conclusions:
We proposed a proof-of-concept study of a multi-level optimization-driven 2D/3D matching scheme to reconstruct 3D fetal postures and associated kinematic patterns from dynamic MRI data during vaginal delivery simulation. It is expected that this novel dataset will make a potential contribution to the future model development and evaluation of the childbirth process.
