Sharpening the Ensemble: An SSIM-Aligned Residual Refiner for Brain-MRI Inpainting Post-Processing

arXiv:2609.03981 · cs.CV, cs.LG · Submitted 2026-09-03 · Read on arXiv

cs.CV, cs.LG

Submitted: 2026-09-03

Updated: 2026-09-03

Terminology

• Benchmark — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Accuracy — 3× in this paper · explained in 1 episode
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification
• MONAI: An open-source framework for deep learning in healthcare
• The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting
• Post-Processing Methods for Improving Accuracy in MRI Inpainting
• Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge
• U-Net Based Healthy 3D Brain Tissue Inpainting
• Robust 3D Brain MRI Inpainting with Random Masking Augmentation

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