SimNICT is the first comprehensive dataset for training universal non-ideal measurement CT (NICT) enhancement models, containing simulated low-dose, limited-angle, and sparse-view CT from different body regions.
We release the SimNICT Dataset (823 GB, 8 datasets) for comprehensive NICT research, and provide SimNICT-AMOS-Sample (78 MB) for quick exploration and prototyping.
💡 Recommendation: Start with SimNICT-AMOS-Sample Dataset… See the full description on the dataset page:
https://huggingface.co/datasets/YutingHe-list/SimNICT.
