Research · 2025
4D Flow MRI Hepatic Flow Pipeline
A Python pipeline that extracts and quantifies hepatic flow metrics from 4D Flow MRI to study Fontan hemodynamics and AVM risk.
Role: Researcher — Marsden Cardiovascular Biomechanics Lab
Overview
Fontan patients are prone to hepatic arteriovenous malformations (AVMs), but the hemodynamic signals linked to that risk are buried in large 4D Flow MRI datasets. As a researcher in the Marsden Cardiovascular Biomechanics Lab, I built a Python pipeline that extracts and quantifies hepatic flow metrics from 4D Flow MRI scans using NumPy and SciPy, applies signal processing and pattern recognition to surface candidate AVM biomarkers, and validates and visualizes the results in Seaborn and Plotly. The pipeline is benchmarked reproducibly with Git/GitHub and Bash-based CI/CD so results can be regenerated and checked as the analysis evolves.
Highlights
- Extract and quantify hepatic flow metrics from 4D Flow MRI using NumPy, SciPy, and Matplotlib.
- Apply signal processing and pattern recognition for AVM biomarker detection, with statistical validation and visualization in Seaborn and Plotly.
- Automate reproducible benchmarking with Git/GitHub, Bash, and CI/CD.
Tech & topics
- Python
- NumPy
- SciPy
- Medical Imaging
- Signal Processing
- Data Visualization