Fetal and Mother Numerical Models (FEMONUM)

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The models distributed in this project are licensed under a Creative Commons Attribution-Noncommercial-Share Alike 2.0 France License.

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Outline of the project

Several international scientific organizations and institutes, such as the World Health Organization (WHO) and the COST 281, have expressed the need for developing numerical models of the human body to enable studies of the interactions between radio-frequency electromagnetic waves and biological tissues. Several previous works have focused on developing models of adults and children heads, based on magnetic resonance imaging (MRI) data. New usage habits of mobile phones (hand free kits, ...) and the introduction of new technologies based on electromagnetic fields (Wifi, ...) have raised the need to develop whole body numerical models, based on medical images. With the advent of obstetrical imaging, models of the fetus and the pregnant woman are now considered.

This project, entitled FEMONUM (FEtus and MOther NUmerical Models), aims at providing numerical models generated from a large database of imaging exams. The proposed models, evaluated by an obsterician and a group of pediatric radiologists, enable precise dosimetry studies on the complex, highly variable and evolving anatomy of the pregnant woman.
This project was funded by the Fondation Santé et Radiofréquence. The numerical models are made available to the scientific community, filling an important gap in the list of existing human body models. The modeling approach is based on medical image segmentation and smooth surface mesh generation. Two types of medical imaging modalities were used to screen and model the fetus:

3D Ultrasound data for fetuses during the 1st trimester.
MRI data for fetuses during the 2nd and 3rd trimesters.

3D Ultrasound Segmentation

A database of 3D ultrasound image volumes was provided by collaborating obstetricians, (Hospital Beaujon, Paris, FRANCE). Segmentation of the fetus body was performed in two steps:

As a first step, we distinguish the amniotic fluid from maternal and fetal tissues. An automated segmentation framework based on statistical homogeneity measures was designed to perform this task. This work was published in the proceedings of the 5th International Symposium on Biomedical Imaging (ISBI'2008), pp 17-20, Paris, France, May 14-17, 2008


3D Ultrasound image	Segmentation	3D reconstruction of the fetus body

As second step, segmentation errors and connections between the fetus and the uterine wall were manually corrected to generate a final mesh model.

(blue) field of view, (pink) uterine internal wall,

(yellow) fetus body.

MRI Segmentation

MRI image data provide a clear visualization of several maternal abdominal tissues (skin, bone, fat, muscles,...) and of fetal organs (body envelope, brain, lungs, heart,...).

In collaboration with the pediatric radiology department of the hospital Saint Vincent de Paul (Paris, France), we first performed a study to define the best suited MRI protocol for the segmentation and modeling of the fetus. The Steady State Free Precession was selected, offering the best image quality for the segmentation task. Results of this study were published in the proceedings of the 29th Engineering in Medicine and Biology Conference (EMBC'2007), pp 771-774, Lyon, France, Aug 23-26, 2007.

A methodological framework was developed for automated segmentation of several fetal structures, including the eyes, the brain-skull content, the spinal cord, the urinary bladder, and the fetal envelope. The segmentation process is based on the extraction of landmark points based on appearance models, iterative orientation of the fetus based on the landmark points and fine segmentation of tissue interfaces with a contrast-sensitive graph-cut partitioning of image data, within narrow bands of image data. This work was published in the proceedings of the 7th International Symposium on Biomedical Imaging (ISBI'2010), Rotterdam, Netherlands, April 14-17, 2010.


SSFP MRI image of a fetus	3D fetus segmentation

Pregnant Woman Body

Victoria is a non-gravid woman body envelope mesh model developed by Daz Studio, which can be manipulated and animated with the software Blender.

We used Victoria's body envelope to generate hybrid models of pregrant women:

For models based on 3D ultrasound data, the abdominal surface of Victoria was not modified.
For models based on MRI data, the abdominal surface of Victoria was deformed applying a series of automatically computed and controlled deformations using a physics-based interactive modeler.

The modeler was developed with the Computational Geometry Algorithms Library, CGAL, and the open-source medical simulation framework SOFA. Firstly, we created a hexahedral finite element model (FEM) from Victoria's body envelope. Then, the uterus was scaled down and positioned inside Victoria's body using three bone landmark points. It was then progressively scaled up to its original size using a collision-detection physical deformation model. Collisions between the mother skin and the uterus were detected, the involved forces were computed and the position of the models was updated according to the reverse forces effects. This method allowed us to maintain a minimal distance of approximately 16 millimeters between the uterus and the mother skin (according to obstetrical data). This work was published in the proceedings of the 5th International Symposium on Biomedical Simulation (ISBMS'2010), Phoenix, United States, January 23-24, 2010.


Mesh-based pregnant woman model (fetal model based on MRI data). (Left) 33 weeks of amenhorea. Sagittal position. (Right) 35 weeks of amenhorea. Sagittal position. Twin pregnancy.

Pixel-based models were finally generated, at a desired spatial resolution, with different labels assigned to the different tissues.


Pixel-based pregnant woman model

This project was funded by the Fondation Santé et Radiofréquences, the Instituts Carnot and Orange.