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SimNICT / README.md
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metadata
license: cc-by-nd-4.0
size_categories:
  - n>1T
tags:
  - medical
dataset_info:
  features:
    - name: ICT
      dtype: image
    - name: LDCT_Low
      dtype: image
    - name: LDCT_Mid
      dtype: image
    - name: LDCT_High
      dtype: image
    - name: LACT_Low
      dtype: image
    - name: LACT_Mid
      dtype: image
    - name: LACT_High
      dtype: image
    - name: SVCT_Low
      dtype: image
    - name: SVCT_Mid
      dtype: image
    - name: SVCT_High
      dtype: image
  splits:
    - name: train_previews
      num_bytes: 62199112
      num_examples: 44
    - name: test_previews
      num_bytes: 16108271
      num_examples: 11
  download_size: 153191938
  dataset_size: 78307383
configs:
  - config_name: default
    data_files:
      - split: train_previews
        path: data/train_previews-*
      - split: test_previews
        path: data/test_previews-*

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.

Citation