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, 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 | 459 | 118,119 | CC BY 4.0 |
| STOIC | Grand Challenge | 2,000 | 867,376 | CC BY 4.0 |
| MELA | Grand Challenge | 1,100 | 496,673 | CC BY 4.0 |
| LUNA | Grand Challenge | 888 | 227,225 | CC BY 4.0 |
| LNDb | Grand Challenge | 294 | 94,153 | CC BY 4.0 |
| HECKTOR22 | Grand Challenge | 883 | 200,100 | |
| CT_COLONOGRAPHY | TCIA | 1,730 | 938,082 | CC BY 3.0 |
| AutoPET | Grand Challenge | 1,014 | 560,796 | |
| AMOS | Grand Challenge | 500 | 76,679 | CC BY 4.0 |
| CT Images in COVID-19 | TCIA | 771 | 54,262 | CC BY 4.0 |
Ongoing
- Release the SimNICT dataset containing 10.6 million NICT-ICT image pairs.
- Release the SimNICT-AMOS-Sample dataset, a subset of the SimNICT dataset.