Update README.md

README.md

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 # SimNICT: Simulated Non-Ideal measurement CT Dataset
 
 **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.
 
-We open source the **[SimNICT Dataset](#part-1-simnict-dataset)** (~823 GB, 8 datasets) for comprehensive NICT research with a subset **[SimNICT-AMOS-Sample Dataset](#part-2-simnict-amos-sample)** (~78 MB) for quick exploration and prototyping.
-
-**💡 Recommendation**: Start with **SimNICT-AMOS-Sample** for initial exploration and prototyping, then download specific datasets from the **SimNICT Dataset** based on your research needs.
+**💡 Recommendation**: Start with [SimNICT-AMOS-Sample Dataset](#part-2-simnict-amos-sample) for initial exploration and prototyping, then download specific datasets from the [SimNICT Dataset](#part-1-simnict-dataset) based on your research needs.
 
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@@ -106,8 +105,6 @@ python simnict_download.py --datasets AMOS LUNA --output_dir ./data
 
 After downloading preprocessed ICT data, generate NICT data with the following simulation code to construct complete SimNICT dataset:
 
-**📋 Simulation Usage:**
-
 ```python
 # Download simulation code
 wget https://huggingface.co/datasets/YutingHe-list/SimNICT/blob/main/simnict_generator.py