Analysis Result AI-derived annotations for the NLST and NSCLC-Radiomics computed tomography imaging collections
Details
Subject Count: 985
Primary Site: Chest, Lung
Analysis Artifacts: SEG, SR
Cancer Type(s): Lung Cancer, Non-Cancer
DOIs
nnU-Net-BPR-annotations 10.5281/zenodo.7473970
Collections analyzed:
Description
Public imaging datasets are critical for the development and evaluation of automated tools in cancer imaging. Unfortunately, many of the available datasets do not provide annotations of tumors or organs-at-risk, crucial for the assessment of these tools. This is due to the fact that annotation of medical images is time consuming and requires domain expertise. It has been demonstrated that artificial intelligence (AI) based annotation tools can achieve acceptable performance and thus can be used to automate the annotation of large datasets. As part of the effort to enrich the public data available within NCI Imaging Data Commons (IDC) (https://imaging.datacommons.cancer.gov/) [1], we introduce this dataset that consists of such AI-generated annotations for two publicly available medical imaging collections of Computed Tomography (CT) images of the chest.
Please see the nnU-Net-BPR-annotations description page to learn more about the images and to obtain any supporting metadata for this collection.