Research · Jan 2026 – Present
Medical-to-Medical Image Generation
GANsPyTorchDiffusion
CORE FEATURES
- Modality translation (MRI <-> CT).
- Denoising Diffusion models optimized for volumetric medical imaging.
- Structural Similarity Index (SSIM) of > 0.94 achieved on clinical validation sets.
PROJECT OVERVIEW.
High-fidelity medical modality translation using generative deep learning. This project translates MRI scans to CT scans (and vice versa) utilizing dual-generator GANs and DDPMs (Denoising Diffusion Probabilistic Models), reducing scan times and costs while preserving pixel-perfect anatomical structures.
DEVELOPMENT & SYSTEM ARCHITECTURE.
Built from the ground up prioritizing speed, reliability, and modular abstractions. Employs modern pipelines to handle telemetry data, neural state machines, and real-time inputs, verifying constraints at build-time and ensuring minimal runtime overhead.