The Second International Workshop on Pulmonary Image Analysis

M. Brown, M. de Bruijne, B. van Ginneken, A. Kiraly, J. Kuhnigk, C. Lorenz, J. McClelland, K. Mori, A. Reeves and J. Reinhardt


After the successful first edition of the International Workshop on Pulmonary Image Analysis at MICCAI 2008 in New York City, the entire organizing team volunteered to organize the second edition of this event, aimed at bringing together researchers in pulmonary image analysis to discuss recent advances in this rapidly developing field. The Second International Workshop on Pulmonary Image Analysis will be held on September 20, 2009 in London, UK, again as a workshop of the MICCAI conference. Two researchers later joined the organizing team. We received many high quality submissions for this workshop. All papers underwent a thorough review process with two to four reviews per paper by members of the program committee and additional reviewers. The proceedings of this workshop consist of three parts. There are fifteen regular papers, dealing with various aspects of image analysis of pulmonary image data, including segmentation, registration, and quantification of abnormalities in various modalities, with the focus in most studies on computed tomography, but also with papers on the analysis of MRI and X-ray scans. Next to these regular papers, we invited researchers to join in two comparative studies where algorithms were applied to a common data set, and submit a paper to the workshop about their system. The first of these challenges is EXACT09, on the extraction of the pulmonary airway tree from CT data. The second one, VOLCANO'09, is on the analysis of size changes in pulmonary nodules from consecutive CT scans. The results of these challenges are described in two overview papers that can be found in these proceedings. Moreover, fifteen papers describe systems that participated in the EXACT09 challenge and three papers describe algorithms that were used for the VOLCANO'09 challenge. That challenge attracted thirteen participating teams who applied algorithms, often previously published and not described in these proceedings, to the challenge data.