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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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TotalSegmentator-CT-Segmentations: TotalSegmentator segmentations and radiomics features for NCI Imaging Data Commons CT images

Authors: Thiriveedhi, Vamsi Krishna; Krishnaswamy, Deepa; Clunie, David; Fedorov, Andrey;

TotalSegmentator-CT-Segmentations: TotalSegmentator segmentations and radiomics features for NCI Imaging Data Commons CT images

Abstract

This dataset contributes volumetric segmentations of the anatomic regions in a subset of CT images available from NCI Imaging Data Commons [1] (https://imaging.datacommons.cancer.gov/) automatically generated using the TotalSegmentation model v1.5.6 [2]. The initial release includes segmentations for the majority of the CT scans included in the National Lung Screening Trial (NLST) collection [3], [4] already available in IDC. Direct link to open this analysis result dataset in IDC (available after release of IDC v18): https://portal.imaging.datacommons.cancer.gov/explore/filters/?analysis_results_id=TotalSegmentator-CT-Segmentations. Specifically, for each of the CT series analyzed, we include segmentations as generated by TotalSegmentator, converted into DICOM Segmentation object format using dcmqi v1.3.0 [5], and first order and shape features for each of the segmented regions, as produced by pyradiomics v3.0.1 [6]. Radiomics features were converted to DICOM Structured Reporting documents following template TID1500 using dcmqi. TotalSegmentator analysis on the NLST cohort was executed using Terra platform [7]. Implementation of the workflow that was used for performing the analysis is available at https://github.com/ImagingDataCommons/CloudSegmentator [8]. Due to the large size of the files, they are stored in the cloud buckets maintained by IDC, and the attached files are the manifests that can be used to download the actual files. If you use the files referenced in the attached manifests, we ask you to cite this dataset and the preprint describing how it was generated [9]. Download instructions Each of the manifests include instructions in the header on how to download the included files. To download the TotalSegmentator segmentations (in DICOM SEG format) and pyradiomics measurements (in DICOM SR format) files using .s5cmd manifests: install idc-index package: pip install --upgrade idc-index download the files referenced by manifests included in this dataset by passing the .s5cmd manifest file. E.g., idc download totalsegmentator_ct_segmentations_aws.s5cmd Other files included in the record are: firstorder and shape radiomics features extracted using pyradiomics, and organized one file per segmented structure (see README file in the zip file for details on how those are organized) pyradiomics_features_csv.zip: saved in CSV format pyradiomics_features_parquet.zip: saved in Parquet format Support If you have any questions about this dataset, or if you experience any issues, please reach out to Imaging Data Commons support via support@canceridc.dev or (preferred) IDC Forum at https://discourse.canceridc.dev.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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Cancer Research