BrainGrowth

Table of Contents

• Introduction
• Requirements
• Configuration of Parameters and Run

Introduction

This repository contains the work during the PhD of Xiaoyu WANG, titled "Brain development analysis using MRI and physical modeling".

Requirements

All scripts were coded in python 2.7, but they are compatible to python 3.7 (tested on the version 3.7.3).

Python packages and versions

• enum34==1.1.6
• funcsigs==1.0.2
• llvmlite==0.24.0
• nibabel==2.5.1
• numba==0.39.0
• numpy==1.17.2
• numpy-stl==2.10.1
• python-utils==2.3.0
• scikit-learn==0.21.3
• scipy==1.3.1
• singledispatch==3.4.0.3
• six==1.12.0
• Vapory==0.1.1
• mpmath==1.0.0
• os
• trimesh
• slam

The file called requirements.txt helps to install all the python libraries.

• Using pip:

pip install -r requirements.txt

Configuration of Parameters and Run

simulation.py

Example of dynamic simulations of a neo-Hookean solid with a tangential differential growth.

python simulation.py -i './data/sphere5.mesh' -o './res/sphere5' -hc 'whole' -t 0.042 -g 1.829 -gm 'global'

i: path of input maillage

o: path of output

hc: whole or half geometry

t: cortical thickness

g: relative growth rate

gm: global or regional growth

Running a demo

In simulation.py, there are certain parameters should be set manually:

a: average mesh spacing

For sphere5.mesh:

a = 0.01

Input mesh image， output dynamic process

Publications

Wang, X., Lefèvre, J., Bohi, A. et al. The influence of biophysical parameters in a biomechanical model of cortical folding patterns. Sci Rep 11, 7686 (2021). https://doi.org/10.1038/s41598-021-87124-y