Visualize velocity image series from a phase contrast magnetic resonance imaging study as a three-dimensional vector field.

Clone the repository

git clone https://github.com/lewinkoon/hemoflow

Change into the project directory

cd hemoflow

Create a virtual environment inside the directory

python -m venv .venv

Activate the previously created virtual environment

.venv\Scripts\activate # on Windows
source .venv/bin/activate # on Unix or MacOS

Install poetry dependency manager

python -m pip install poetry

Install the required dependencies for the project

poetry install

Create the required file directories

hemoflow init

The four directories correspond with the following image series:

• FH - Feet to head flow images.
• AP - Anterior to posterior flow images.
• RL - Right to left flow images.

Copy your dicom image series to files/ directory.

files/
├───FH
│   ├───IM1.DCM
│   ├───IM2.DCM
│   ├───...
│   └───IMX.DCM
├───AP
│   ├───IM1.DCM
│   ├───IM2.DCM
│   ├───...
│   └───IMX.DCM
└───RL
    ├───IM1.DCM
    ├───IM2.DCM
    ├───...
    └───IMX.DCM

Finally, build volumetric the velocity field from dicom files.

hemoflow build

Data files in .csv format will be created for each timestep in output/ folder.

output/
├───data.csv.0
├───data.csv.26
├───...
└───data.csv.603

Each dataframe will have cordinates and velocity components for each axis.

This project is licensed under the MIT License. See license.txt file for details.