This paper provides a comprehensive review of 3D medical scene completion techniques developed over the past decade, from 2016 to 2026. It traces the evolution from early voxel-based methods to current approaches integrating generative diffusion models with real-time rendering using Gaussian splatting. The review categorizes advancements across various representation paradigms, including point learning, implicit neural fields, and transformer networks, and identifies ongoing challenges and future research directions. AI
IMPACT Provides a structured overview of advancements in 3D scene completion, potentially guiding future research in AI-driven medical imaging and robotics.
RANK_REASON The item is a systematic review paper published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]
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