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AI Enables Ultra-Low-Dose CT Reconstruction
RPI ID: 2021-072-401
Innovation Summary:
AI-enabled ultra-low-dose CT reconstruction systems use deep learning to restore image quality from low-radiation scans. The models are trained on paired datasets to enhance resolution and contrast while minimizing noise. This approach allows for safer imaging without compromising diagnostic accuracy. It is...
Published: 3/10/2026
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Updated: 3/10/2026
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Inventor(s): Mannudeep Kalra, Chuang Niu, Hengyong Yu, Shadi Ebrahimian, Weiwen Wu, Ge Wang
Keywords(s): deep learning, Deep Tomographic Reconstruction, Few-view, Ultra-low-dose
Category(s): Computational Science and Engineering
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Stabilizing Deep Tomographic Reconstruction Networks
RPI ID: 2021-007-201
Innovation Summary:
A hybrid image reconstruction system combines model-based and data-driven techniques to improve image quality across modalities. The architecture integrates physics-informed priors with deep learning algorithms to reduce noise and artifacts. It supports real-time processing and is adaptable to CT, MRI, and PET...
Published: 3/10/2026
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Updated: 3/10/2026
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Inventor(s): Weiwen Wu, Wenxiang Cong, Hengyong Yu, Ge Wang
Keywords(s): analytic reconstruction, compressed sensing, deep learning, iterative reconstruction, tomographic imaging
Category(s): Computational Science and Engineering
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Translation Based Low-end Computed Tomography
RPI ID: 2014-031-201Innovation Summary:This invention introduces a linear scanning architecture for computed tomography (CT) that eliminates the need for rotational gantries. The system uses linearly translating X-ray sources and detectors moving in opposite or near-opposite directions. This arrangement enables tomographic imaging in environments where...
Published: 9/4/2025
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Updated: 9/4/2025
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Inventor(s): Wenxiang Cong, Fenglin Liu, Ge Wang, Hengyong Yu
Keywords(s):
Category(s): Biotechnology and the Life Sciences
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