introduction: virtual bronchoscopy is a reliable and efficient diagnostic method for primary symptoms of lung cancer. the segmentation of airways from ct images is a critical step for numerous virtual bronchoscopy applications. materials and methods: to overcome the limitations of the fuzzy connectedness method, the proposed technique, called fuzzy connectivity - fuzzy c-mean (fc-fcm), utilized...

Introduction: Virtual bronchoscopy is a reliable and efficient diagnostic method for primary symptoms of lung cancer. The segmentation of airways from CT images is a critical step for numerous virtual bronchoscopy applications. Materials and Methods: To overcome the limitations of the fuzzy connectedness method, the proposed technique, called fuzzy connectivity - fuzzy C-mean (FC-FCM), utilized...

Inflammatory and infectious lung diseases commonly involve bronchial airway structures and morphology, and these abnormalities are often analyzed non-invasively through high resolution computed tomography (CT) scans. Assessing airway wall surfaces and the lumen are of great importance for diagnosing pulmonary diseases. However, obtaining high accuracy from a complete 3-D airway tree structure c...

Lung diseases such as COPD and asthma affect airway morphology. Automated segmentation is an essential first step toward the analysis of airways. We propose a fully-automated algorithm to segment the airway tree from chest CT scans. The proposed algorithm requires no manual intervention and uses a 3D region growing based method and allows for accurate detection of leakage by growing regions wit...

In this paper a new approach to CT based investigation of pulmonary airways is introduced. Especially a new fully automated algorithm for airway tree segmentation is proposed. The algorithm is based on 3D seeded region growing. However in opposite to traditional approaches region growing is applied twice: firstly – for detecting main bronchi, secondly – for localizing low order parts of the air...

We propose algorithms to automate the segmentation of pulmonary tree structures in the lung, using tools from Mathematical Morphology. This involves segmenting three diierent types of three-dimensional tree structures (airway tree, pulmonary artery, pulmonary vein) from a stack of grayscale Computed Tomography (CT) images. The proposed algorithms rely on the grayscale reconstruction operator to...

The segmentation of the human airway tree from volumetric multidetector-row computed tomography images is an important prerequisite for many clinical applications and physiologic studies. We present a new airway segmentation method based on fuzzy connectivity. Small adaptive regions of interest are used that follow the airway branches as they are segmented. This method works on various types of...

PURPOSE To develop an automated pulmonary image analysis framework for infectious lung diseases in small animal models. METHODS The authors describe a novel pathological lung and airway segmentation method for small animals. The proposed framework includes identification of abnormal imaging patterns pertaining to infectious lung diseases. First, the authors' system estimates an expected lung ...

Airway segmentation and analysis is an essential step in the understanding of pulmonary anatomy and early detection of lung diseases. In this paper, we evaluate a newly developed method for segmenting the inner and outer surfaces of the airway tree. This is the first approach reported to validate the segmentation of the double wall surfaces for the entire airway tree including bifurcations. Two...

Some lung diseases are related to bronchial airway structures and morphology. Although airway segmentation from chest CT volumes is an important task in the computer-aided diagnosis and surgery assistance systems for the chest, complete 3-D airway structure segmentation is a quite challenging task due to its complex tree-like structure. In this paper, we propose a new airway segmentation method...