PathoSyn: AI for MRI Image Synthesis
Published:Dec 29, 2025 01:13
•1 min read
•ArXiv
Analysis
This paper introduces PathoSyn, a novel generative framework for synthesizing MRI images, specifically focusing on pathological features. The core innovation lies in disentangling the synthesis process into anatomical reconstruction and deviation modeling, addressing limitations of existing methods that often lead to feature entanglement and structural artifacts. The use of a Deviation-Space Diffusion Model and a seam-aware fusion strategy are key to generating high-fidelity, patient-specific synthetic datasets. This has significant implications for developing robust diagnostic algorithms, modeling disease progression, and benchmarking clinical decision-support systems, especially in scenarios with limited data.
Key Takeaways
- •PathoSyn is a novel generative framework for MRI image synthesis.
- •It disentangles anatomical reconstruction and deviation modeling.
- •Uses a Deviation-Space Diffusion Model for pathological residuals.
- •Aims to improve diagnostic algorithms and disease modeling.
- •Outperforms existing methods in perceptual realism and anatomical fidelity.
Reference
“PathoSyn provides a mathematically principled pipeline for generating high-fidelity patient-specific synthetic datasets, facilitating the development of robust diagnostic algorithms in low-data regimes.”