@inproceedings{6a74db1a2a82462cbac97ed06a6ddd49,
title = "Robust method for extracting the pulmonary vascular trees from 3D MDCT images",
abstract = "Segmentation of pulmonary blood vessels from three-dimensional (3D) multi-detector CT (MDCT) images is important for pulmonary applications. This work presents a method for extracting the vascular trees of the pulmonary arteries and veins, applicable to both contrast-enhanced and unenhanced 3D MDCT image data. The method finds 2D elliptical cross-sections and evaluates agreement of these cross-sections in consecutive slices to find likely cross-sections. It next employs morphological multiscale analysis to separate vessels from adjoining airway walls. The method then tracks the center of the likely cross-sections to connect them to the pulmonary vessels in the mediastinum and forms connected vascular trees spanning both lungs. A ground-truth study indicates that the method was able to detect on the order of 98% of the vessel branches having diameter ≥ 3.0 mm. The extracted vascular trees can be utilized for the guidance of safe bronchoscopic biopsy.",
author = "Pinyo Taeprasartsit and Higgins, {William E.}",
year = "2011",
doi = "10.1117/12.876721",
language = "English (US)",
isbn = "9780819485045",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
booktitle = "Medical Imaging 2011",
note = "Medical Imaging 2011: Image Processing ; Conference date: 14-02-2011 Through 16-02-2011",
}