<title>Quantitative 3D reconstruction of airway and pulmonary vascular trees using HRCT</title>

Abstract

Accurate quantitative measurements of airway and vascular dimensions are essential to evaluate function in the nonnal and diseased lung. In this report, a novel method is dexcribed for three-dimensional extraction and analysis of pulmonary tree structures using data from High Resolution Computed Tomography (HRCT). Serially scanned two-dimensional slices of the lower left lobe of isolated dog lungs were stacked to create a volume of data. Airway and vascular trees were threedimensionally extracted using a three dimensional seeded region growing algorithm based on differences in CT number between wall and lumen. To obtain quantitative data, we re4uced each tree to its central axis. From the central axis, branch length is measured as the distance between two successive branch points, branch angle is measured as the angle produced by two daughter branches, and cross sectional area is measured from a plane perpendicular to the central axis point. Data derived from these methods can be used to localize and quantify structural differences both during changing physiologic conditions and in pathologic lungs.

<title>Knowledge-based segmentation of intrathoracic airways from multidimensional high-resolution CT images</title>

“…Due to partial volume effect only a few branches were reconstructed. In [7], three-dimensional seeded region growing was used on data from an isolated lobe of a dog lung that was processed under seven static pressures ranging from 0.3 kPa (inspiration) to 2.0 kPa (expiration). After extraction of the airway tree, the central axis of each branch was obtained, filtered, and bifurcation points were detected.…”

“…Gray-level based techniques using three-dimensional seeded region growing [4,5,6,7] work well in major pulmonary tree branches. Using 3-D connectivity, a contiguous volume connected to the manually identified location in the mainstem bronchus is extracted and represents the primary tree.…”

“…three-dimensional seeded region growing[4,5,6] as described in[7] was used for comparison.78/SPIE Vol. 2168 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/16/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx…”

Segmentation of intrathoracic airway trees: a fuzzy logic approach

“…The gray levels of large diameter airways fall within a tight gray-value range in CT images and differ significantly from the airway walls, thus exhibiting high-contrast borders [4], [12]. Using 3-D connectivity, a contiguous volume connected to the tree root (trachea) represents the primary tree.…”

“…Ney presented 3-D visualization of bronchial and vascular pulmonary trees from fixed lung CT image datasets [3]. Wood et al applied 3-D seeded region growing to data from an isolated lobe of a dog lung that was processed under seven static pressures [4], [5] and performed physiological measurements such as obtaining airway-tree segment lengths, branching angles, and cross-sectional areas of the branches. While quite useful for segmentation of isolated lung specimens, we have found the above methods to be unreliable when applied to CT image data in vivo.…”