ABSTRACT
Lung cancer remains the leading cause of cancer-related death in the United States. In 2006, there were approximately 174,470 new cases of lung cancer and 162,460 related deaths [1]. Early diagnosis of cancer can improve the effectiveness of treatment and increase the patient’s chances of survival. Segmentation of the lung tissues is a crucial step for developing any computer-assisted diagnostic system for early diagnosis of lung cancer. Accurate segmentation of lung tissues from low-dose computed tomography (LDCT) images is a challenging problem because some lung tissues such as arteries, veins, bronchi, and bronchioles are very close to the chest tissues. Therefore, segmentation cannot be based only on image signals but should also account for spatial relationships between the region labels to preserve the details of the lung region.
