The LUNA25 Challenge: Public Training and Development set - Imaging Data

This dataset represents the imaging part of LUNA25: Public Training and Development dataset. In total, it contains 2120 patients and 4069 low-dose chest CT scans (luna25_images.zip.XXX), with 555 annotated malignant nodules and 5608 benign nodules (luna25_nodule_blocks.zip.XXX). The dataset was acquired in participants who enrolled in the National Lung Cancer Screening Trial (NLST) between 2002 and 2004 in one of the 33 centers in the United States. The LUNA25 challenge is new grand challenge designed to evaluate the diagnostic performance of AI algorithms and radiologists in lung nodule malignancy risk estimation in screening CT. LUNA25 aims to establish: 1) state-of-the-art AI performance for lung nodule malignancy risk estimation, 2) performance of radiologists at lung nodule malignancy risk estimation through a large scale international reader study, 3) a comparison between performance of AI algorithms and radiologists with a variety of experience levels. This study hypothesizes that state-of-the-art AI is non-inferior to radiologists at lung nodule malignancy risk estimation at screening CT. This is a derivative of the original NLST DICOM dataset, also provided under a CC-BY 4.0 license: National Lung Screening Trial Research Team. (2013). Data from the National Lung Screening Trial (NLST) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.HMQ8-J677)