About

This is a derivative of the TotalSegmentator dataset.

1228 CT images and corresponding segmentation mask of 117 structures We combined multiple segmentation masks into a single nii.gz file under the folder Masks, and moved all CT images to the folder Images. All images and masks are renamed according to case IDs.

This dataset is released under the CC-BY-4.0 license.

  Official Release

GitHub (official): https://github.com/wasserth/TotalSegmentator (Apache-2.0… See the full description on the dataset page: https://huggingface.co/datasets/YongchengYAO/TotalSegmentator-CT-Lite.

Dataset

This dataset was created by Elahi

Contents

Background: The aggressive and heterogeneous nature of lung cancer has thwarted efforts to reduce mortality from this cancer through the use of screening. The advent of low-dose helical computed tomography (CT) altered the landscape of lung-cancer screening, with studies indicating that low-dose CT detects many tumors at early stages. The National Lung Screening Trial (NLST) was conducted to determine whether screening with low-dose CT could reduce mortality from lung cancer.

Methods: From August 2002 through April 2004, we enrolled 53,454 persons at high risk for lung cancer at 33 U.S. medical centers. Participants were randomly assigned to undergo three annual screenings with either low-dose CT (26,722 participants) or single-view posteroanterior chest radiography (26,732). Data were collected on cases of lung cancer and deaths from lung cancer that occurred through December 31, 2009. This dataset includes the low-dose CT scans from 26,254 of these subjects, as well as digitized histopathology images from 451 subjects.

Results: The rate of adherence to screening was more than 90%. The rate of positive screening tests was 24.2% with low-dose CT and 6.9% with radiography over all three rounds. A total of 96.4% of the positive screening results in the low-dose CT group and 94.5% in the radiography group were false positive results. The incidence of lung cancer was 645 cases per 100,000 person-years (1060 cancers) in the low-dose CT group, as compared with 572 cases per 100,000 person-years (941 cancers) in the radiography group (rate ratio, 1.13; 95% confidence interval [CI], 1.03 to 1.23). There were 247 deaths from lung cancer per 100,000 person-years in the low-dose CT group and 309 deaths per 100,000 person-years in the radiography group, representing a relative reduction in mortality from lung cancer with low-dose CT screening of 20.0% (95% CI, 6.8 to 26.7; P=0.004). The rate of death from any cause was reduced in the low-dose CT group, as compared with the radiography group, by 6.7% (95% CI, 1.2 to 13.6; P=0.02).

Conclusions: Screening with the use of low-dose CT reduces mortality from lung cancer. (Funded by the National Cancer Institute; National Lung Screening Trial ClinicalTrials.gov number, NCT00047385).

Data Availability: A summary of the National Lung Screening Trial and its available datasets are provided on the Cancer Data Access System (CDAS). CDAS is maintained by Information Management System (IMS), contracted by the National Cancer Institute (NCI) as keepers and statistical analyzers of the NLST trial data. The full clinical data set from NLST is available through CDAS. Users of TCIA can download without restriction a publicly distributable subset of that clinical data, along with the CT and Histopathology images collected during the trial. (These previously were restricted.)

LUNA25 TS Segmentations

The LUNA25 challenge serves as a benchmark for evaluating lung nodule detection in low-dose CT scans. This repository includes segmentations generated using TotalSegmentator for the total, lung_vessels, and lung_nodules tasks. Note: Segmentation volumes have not been independently verified and are supplied "as is".

  Steps to recreate

Use scripts/convert_nifti.py and scripts/convert_nifti.sh to convert LUNA25 .mha files to .nii.gz. Install… See the full description on the dataset page: https://huggingface.co/datasets/farrell236/LUNA25_ts_seg.