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3D CT-to-PET Translation via Latent Brownian Bridge Diffusion
Computed tomography (CT) and positron emission tomography (PET) provide complementary anatomical and functional information for cancer diagnosis and treatment planning. However, the widespread use of PET is limited by high radiation exposure, elevated costs, and restricted availability. To address these limitations, deep learning-based CT-to-PET translation has emerged as a promising approach for synthesizing PET-like information directly from CT images, although accurately modeling the large cross-modal gap remains challenging. In this work, we propose a 3D CT-to-PET translation framework bas
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- arXiv · AI, language, vision and robotics · 2026-09-11T13:47:50.000Z
First collected: 2026-09-20T18:22:04.777Z. This is not the publication date.