Standardized representation of the LIDC annotations using DICOM

Abstract

The Lung Imaging Data Consortium and Image Database Resource Initiative (LIDC) conducted a multisite reader study that produced a comprehensive database of Computed Tomography (CT) scans for over 1000 subjects annotated by multiple expert readers. The result is hosted in the LIDCIDRI collection of The Cancer Imaging Archive (TCIA). Annotations that accompany the images of the collection are stored using projectspecific XML representation. This complicates their reuse, since no generalpurpose tools are available to visualize or query those objects, and makes harmonization with other similar type of data nontrivial. To make the LIDC dataset more FAIR (Findable, Accessible, Interoperable, Reusable) to the research community, we prepared their standardized representation using the Digital Imaging and Communications in Medicine (DICOM) standard. This manuscript is intended to serve as a companion to the dataset to facilitate its reuse.