A method of lung segmentation based on low dose CT images
WU Liang
Lü Xiaoqi
GU Yu
LI Jing
ZHANG Wenli
REN Guoyin
ZHANG Wei
Abstract：To improve the accuracy of computer-aided detection of pulmonary nodules in early lung cancer screening,a fully au-tomatic 3-D lung parenchyma segmentation algorithm based on hybrid processing was presented.Firstly, the low dose CT images were preprocessed by using the improved multi-directional morphological filtering algorithm.Secondly, the rough segmented images were a-chieved using cluster method and flood-fill algorithm to remove the background.Then trachea and the main bronchus tree were re-moved using improved 3D region with hough transform.Finally the fine segmented image was achieved by using watershed and two di-mension convex hull algorithm.50 low dose CT images in the ELCAP database were collected to segment the lung parenchyma with u-sing the proposed method, obtaining the 95.75%of accuracy.The proposed algorithm can provide some valuable information for pul-monary nodule detection.
Keywords：Lung parenchyma segmentationLow dose CTHough transformAlgorithm of convexhullWatershedDetection
Publication Date：2018-01-01
Online Publishing Date：2026-09-11(First online date of this platform, not the publication date of the document)
Pages：5( 163-167 )