Keywords: Other AI/ML, Machine Learning/Artificial Intelligence, image conversion, MR to CT conversion, image synthesis
Motivation: Using deep learning to improve the soft tissue contrast in low-dose brain CT similar to MRI.
Goal(s): Converting low-dose brain CT to high-resolution T1-MPRAGE-like Images.
Approach: A ResUNet-based deep learning approach is developed to learn the complex transformation from low-dose brain CT to its corresponding T1-MPRAGE.
Results: With the proposed approach, we obtained high-resolution MR T1-MPRAGE-like images with superior soft-tissue contrasts from noisy low-dose brain CT images.
Impact: By transferring brain CT to T1-MPRAGE-like images, our approach provides superior soft tissue contrast from low-dose brain CT images. Our method would allow tissue-specific analysis using noisy non-contrast CT.
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