|
--- |
|
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. --> |
|
|
|
|
