Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in CT images

Automatic detection of pulmonary nodules in thoracic computed tomography (CT) scans has been an active area of research for the last two decades. However, there have only been few studies that provide a comparative performance evaluation of different systems on a common database. The evaluation of different systems using the same framework provides unique information that can be leveraged to further improve the existing systems and develop novel solutions.

Within this project, we have set up the LUNA16 challenge, an objective evaluation framework for automatic nodule detection algorithms using the largest publicly available reference database of chest CT scans, the LIDC-IDRI data set. The results were presented through a publication listed below and summarized in my PhD Thesis.

Publications

1. A.A.A. Setio et al., ”Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge”, Medical Image Analysis, 42:1-13, 2017.