DocumentCode :
3573827
Title :
Fully automatic extraction of lung parenchyma from CT scans
Author :
Huan Geng ; Zijian Bian ; Jinzhu Yang ; Wenjun Tan ; Dazhe Zhao
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
fYear :
2014
Firstpage :
5626
Lastpage :
5630
Abstract :
In this paper, a novel fully automatic method of extraction of lung parenchyma is presented. Combining the iterative gray-level thresholds selection and the pulmonary regions extraction with error detection in 2D image, seed points and threshold are fast determined. In consequence, the pulmonary airspace is detected with 3D region growing method. Two steps airways segmentation with additional shape constrained criterion is used to completely remove airways from the airspace. To avoid lungs adhesion, the connections are detected and located. The dynamic programming method is applied to separate the left lung and right lung. Twelve clinical studies indicate that the novel method can meet the needs for quantification in diagnosis with respect to accuracy and time requirement.
Keywords :
computerised tomography; diseases; dynamic programming; feature extraction; image segmentation; iterative methods; lung; medical image processing; 2D image; 3D region growing method; CT scans; automatic lung parenchyma extraction; dynamic programming method; iterative gray-level threshold selection; pulmonary airspace segmentation; pulmonary regions extraction; Computed tomography; Educational institutions; Image segmentation; Junctions; Lungs; Shape; Three-dimensional displays; Airways; Lung parenchyma; Region growing; Segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
Type :
conf
DOI :
10.1109/WCICA.2014.7053678
Filename :
7053678
Link To Document :
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