Update README.md

README.md

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-license: cc-by-nd-4.0
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+---
+license: cc-by-nd-4.0
+size_categories:
+- n>1T
+tags:
+- medical
+---
+# SimNICT
+
+- **SimNICT** is the first dataset for training **universal non-ideal measurement CT (NICT)** enhancement models.
+
+- The dataset comprises **over 10.9 million NICT-ICT image pairs**, including low dose CT (LDCT), sparse view CT (SVCT), and limited angle CT (LACT), under varying defect degrees across whole-body regions.
+
+- We have currently uploaded part of the SimNICT dataset, [**SimNICT-AMOS-Sample**](#simnict-amos-sample), with preview images in the dataset viewer. The complete SimNICT dataset will be gradually uploaded in future releases.
+
+
+# SimNICT-AMOS-Sample
+
+- SimNICT-AMOS-Sample dataset contains **55 ICT volumes** from the AMOS dataset in SimNICT, and each ICT volume has been simulated using the same NICT simulation method as in SimNICT, generating **9 types of NICT volumes**.
+
+- This dataset is divided into training and test sets, with 20% and 80% of the total volumes, respectively, to evaluate the performance of our proposed [MITAMP](***) model.
+
+
+# Source Dataset Statistics
+
+- SimNICT starts from the ICT images from ten publicly CT datasets that encompass whole-body regions.
+- By removing low-quality volumes, our SimNICT dataset finally obtains **3,633,465 images** from **9,639 ICT volumes**. 
+
+| Source   | Provenance  | Volume | Slice | License   |
+|-----------------------|-------------------------------------------------------------------------------------------------------------|--------|-----------|--------------------------------------------------------------------------------------------------|
+| COVID-19-NY-SBU        | [TCIA](https://www.cancerimagingarchive.net/collection/covid-19-ny-sbu/)    | 459    | 118,119   | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)    |
+| STOIC                 | [Grand Challenge](https://stoic2021.grand-challenge.org/)   | 2,000  | 867,376   | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)       |
+| MELA                  | [Grand Challenge](https://mela.grand-challenge.org/)    | 1,100    | 496,673   | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)   |
+| LUNA                  | [Grand Challenge](https://luna16.grand-challenge.org/)     | 888    | 227,225   | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)    |
+| LNDb                  | [Grand Challenge](https://lndb.grand-challenge.org/)     | 294    | 94,153    | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)  |
+| HECKTOR22             | [Grand Challenge](https://hecktor.grand-challenge.org/)   | 883    | 200,100   | []()      |
+| CT_COLONOGRAPHY       | [TCIA](https://www.cancerimagingarchive.net/collection/ct-colonography/)     | 1,730  | 938,082   | [CC BY 3.0](https://creativecommons.org/licenses/by/3.0/)     |
+| AutoPET               | [Grand Challenge](https://autopet.grand-challenge.org/)    | 1,014  | 560,796   | []()      |
+| AMOS                  | [Grand Challenge](https://amos22.grand-challenge.org/) | 500    | 76,679    | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)       |
+| CT Images in COVID-19 | [TCIA](https://www.cancerimagingarchive.net/collection/ct-images-in-covid-19/) | 771    | 54,262    | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)       |
+
+
+<!-- # Dataset Structure
+
+- [More Information Needed] -->
+
+# Ongoing
+- [ ] Release the SimNICT dataset containing 10.6 million NICT-ICT image pairs.
+- [x] Release the SimNICT-AMOS-Sample dataset, a subset of the SimNICT dataset.
+
+## Citation
+
+<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+