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.?
The upcoming high-profile?<a href="http://coding4cancer.org/">Coding4Cancer</a>?challenge invites coders to create the best computer algorithm that can identify a person as having lung cancer based on one or multiple low-dose CT images.
To be able to solve the Coding4Cancer challenge, and detect lung cancer in an early stage, pulmonary nodules, the early manifestation of lung cancers, have to be located. 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 publicly available LIDC/IDRI dataset.