2024 WACV WACV 2024

Dual Domain Diffusion Guidance for 3D CBCT Metal Artifact Reduction

Abstract

Previous methods to solve the problem of metal artifact reduction (MAR) have mostly focused on 2D MAR, making it challenging to apply to problems with 3-dimensional CT such as CBCT. In this paper, we propose a novel approach for 3D MAR which utilizes two diffusion models to model the metal-free CBCT prior and metal artifact prior. Through dual-domain guidance in the image and projection domains, the 3D connectivity is enhanced in the restored images. Moreover, we propose a memory-efficient technique for an efficient sampling of 3-dimensional data, which reduces the memory usage by orders of magnitude. Experiments show that our method achieves the state-of-the-art performance not only with synthetic data but also with real-world clinical and out-of-distribution data.

🌉 Interdisciplinary Bridge — Computer Vision and Deep Learning and Healthcare & Medicine
🧭 Keyword Pioneer — 3d ct imaging
🐣 Hot Topic Early Bird — computed tomography
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio