MTF in Practice: 1D, 2D & Frequency-Domain Image Decomposition with Python

📈 MTF in Practice

1D Edge Method • 2D MTF • Frequency-Based Image Reconstruction

Understanding MTF conceptually is one thing.

Seeing it computed — and watching images decompose into frequency components — builds true intuition.

This structured Python package includes:

🔹 1D MTF from ESF

• Simulated edge
• ESF → LSF differentiation
• FFT implementation
• Frequency response interpretation

🔹 2D MTF

• 2D Fourier transform
• Frequency magnitude visualization
• Radial frequency analysis

🔹 Image as Frequency Superposition

• Checkerboard frequency components
• Real image decomposition
• Frequency filtering
• Image reconstruction from selected bands

💻 What You Get

✔ Fully commented Python scripts

✔ Clean visualization pipeline

✔ 1D and 2D implementations

✔ Practical, modifiable examples

✔ Structured for teaching or self-study

🎯 Ideal For

Medical physicists • Imaging physicists • Residents • Students • QA developers

🚀 Why It Matters

MTF connects spatial resolution, sharpness, noise, and reconstruction physics.

This toolkit lets you see those relationships clearly — not just plot a curve.