Researchers have developed WING, a novel generative network designed for cross-modality CT synthesis. This model reformulates the regression target into multiple windowed representations, addressing challenges with direct CT intensity regression. WING utilizes a Gated Inception Generator and a Fuse-and-Refine Transformer to aggregate windowed outputs and refine details, achieving state-of-the-art performance on MRI-to-CT and CBCT-to-CT benchmarks. AI
IMPACT Advances CT synthesis for medical imaging, potentially improving radiotherapy treatment planning and reducing radiation exposure.
RANK_REASON The cluster describes a research paper detailing a new generative network model.
- arXiv
- computed tomography
- cone beam computed tomography
- Fuse-and-Refine Transformer
- Gated Inception Generator
- magnetic resonance imaging
- Wing
- Hugging Face
- Window-Prior-Based Generative Network with Gated Inception
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