| name | quantum-image-encoding-compression |
| description | Gate-efficient quantum medical image encoding using Fourier-based methods. Reduces gates by 4x compared to pixel count. Covers two compression techniques for large-scale medical imaging with negligible quality loss. |
| tags | ["quantum","image-processing","medical","compression"] |
| related_skills | ["quantum-medical-imaging","quantum-feature-encoding"] |
Quantum Medical Image Encoding and Compression
Efficiently encode and compress classical medical images into quantum circuits using Fourier-based methods.
Problem
- Existing encoding methods use gates ≈ 2× number of pixels
- 1024×1024 image = 2M+ gates — computationally prohibitive even for simulation
Solution: Fourier-Based Encoding
Gate Reduction Factor
| Method | Gates | Reduction |
|---|
| Standard (pixel-based) | 2N | baseline |
| Fourier-based | ≤ N/2 | 4× reduction |
Compression Techniques
- Technique 1: Further gate reduction via frequency-domain thresholding
- Technique 2: Pre-processing time reduction with negligible quality loss
Application: Medical Imaging
- Demonstrated on 1024×1024 BABA (Bilateral Axillo-Breast Approach) robotic thyroidectomy images
- Suitable for large-scale medical imaging pipelines
- Maintains diagnostic-quality image fidelity
Workflow
- Input: Classical medical image (e.g., 1024×1024)
- Fourier transform → frequency-domain representation
- Threshold/select significant frequency components
- Encode into quantum circuit with ≤ N/4 gates
- Apply compression if needed
- Process on quantum hardware/simulator
Activation
quantum image encoding, quantum image compression, quantum medical imaging, Fourier quantum encoding, gate-efficient quantum circuits, BABA imaging, quantum image processing, QIMP
References
- arXiv:2505.06471 — "Quantum medical image encoding and compression using Fourier-based methods" (2025)
