About the Workshop

The goal of this workshop is to bring together medical image analysis researchers in the area of thoracic imaging and discuss recent advances in this rapidly developing field. This includes image analysis research for lung and cardiac diseases. The breadth of modalities and the quantity and quality of image data available to study the pulmonary and cardiac system has increased enormously in the last decade. Cardiovascular disease, lung cancer and COPD, three diseases all visible on thoracic imaging, are among the top causes of death worldwide. Recent advances in treatment of lung cancer using immunotherapy lead to substantial increase in prognosis for a subset of patients, but selecting the patients that will profit is a challenge. New drugs to treat idiopathic pulmonary fibrosis (IPF) are able to stop progression of this disease, but are extremely expensive. Image analysis may be a means to select patients that will benefit from these expensive therapies. Other recent developments include the use of spectral CT to better differentiate lung and cardiac tissue types, contrast, and plaque characterization, 4D CT to image lung ventilation and perfusion, hyperpolarized MRI, micro CT for studying the respiratory system in small animals, and the increased use of imaging in radiotherapy planning and treatment.

We invite papers that deal with all aspects of image analysis of these data, including segmentation, registration, quantification, modeling of the image acquisition process, visualization, validation, statistical modeling, biophysical lung modeling (computational anatomy), deep learning and novel applications. The recent success and proliferation of very complex machine (deep) learning models in virtually every field in medical imaging have emphasized the need for good sized independent validation studies. We welcome such studies within the area of thoracic imaging, despite having possibly little technical novelty.


Reinhard R. Beichel
Dept. of Electrical and Computer Engineering, The University of Iowa, Iowa City, USA
Dept. of Internal Medicine, The University of Iowa, Iowa City, USA

Matthew S. Brown
Dept. of Radiological Sciences, David Geffen School of Medicine at UCLA, USA

Colin Jacobs
Dept. of Radiology and Nuclear Medicine, Radboud University Medical Center, The Netherlands

Bianca Lassen-Schmidt
Fraunhofer Institute for Medical Image Computing MEVIS, Bremen, Germany

Kensaku Mori
Information and Communications, Nagoya University, Japan

Jens Petersen
Dept. of Computer Science (DIKU), University of Copenhagen, Denmark

Raul San José Estépar
Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

Alexander Schmidt-Richberg
Philips Research Laboratories Hamburg, Germany

Catarina Veiga
Dept. of Medical Physics and Bioengineering, UCL, UK