Lung cancer remains the leading cause of cancer-related death worldwide. Early detection and diagnosis of cancer can improve the treatment effectiveness. Advancements of lung imaging modalities, for example, low-dose helical CT, cone-beam CT, single photon emission computed tomography (SPECT) and positron emission tomography (PET), and image analysis techniques provide the means of detecting smaller pulmonary nodules at earlier stages than conventional chest radiography. These advanced imaging techniques are also used to address other lung diseases and conditions, such as chronic obstructive lung disease, interstitial lung disease, and pulmonary embolism. The goal of this special issue is to bring together researchers in the area of pulmonary image analysis and discuss the state-of-the-art techniques for automatic detection and computer-aided diagnosis of lung cancer and other lung-related diseases.

All specialists are invited to contribute original research articles as well as reviews that will stimulate the continuing efforts to solve these important problems. Potential topics include, but are not limited to:

• Lung registration
• Lung segmentation
• Vessel segmentation
• Airway segmentation
• Nodule segmentation
• Detection of lung nodules
• Shape analysis of detected nodules
• Appearance analysis of detected nodules
• Diagnosis of lung nodules
• Computer-aided diagnosis of lung diseases

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/ijbi/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/ according to the following timetable: