LUng Nodule Analysis 2016

Lung cancer is the leading cause of cancer-related death worldwide. Screening high risk individuals for lung cancer with low-dose CT scans is now being implemented in the United States and other countries are expected to follow soon. In CT lung cancer screening, many millions of CT scans will have to be analyzed, which is an enormous burden for radiologists. Therefore there is a lot of interest to develop computer algorithms to optimize screening. 

A vital first step in the analysis of lung cancer screening CT scans is the detection of pulmonary nodules, which may or may not represent early stage lung cancer. Many Computer-Aided Detection (CAD) systems have already been proposed for this task. The LUNA16 challenge will focus on a large-scale evaluation of automatic nodule detection algorithms on the LIDC/IDRI data set.

The LIDC/IDRI data set is publicly available, including the annotations of nodules by four radiologists. The LUNA16 challenge is therefore a completely open challenge. We have tracks for complete systems for nodule detection, and for systems that use a list of locations of possible nodules. We provide this list to also allow teams to participate with an algorithm that only determines the likelihood for a given location in a CT scan to contain a pulmonary nodule.

How to Participate

This challenge has been closed. Read more ...


  • Colin Jacobs (Radboud University Medical Center, Nijmegen, The Netherlands)
  • Arnaud Arindra Adiyoso Setio (Radboud University Medical Center, Nijmegen, The Netherlands)
  • Alberto Traverso (Polytechnic University of Turin and Turin Section of INFN, Turin, Italy)
  • Bram van Ginneken (Radboud University Medical Center, Nijmegen, The Netherlands)


For questions, please email Colin Jacobs or Bram van Ginneken.