Title
Automatic lung lobe segmentation of COPD patients using iterative B-spline fitting
Abstract
We present an automatic lung lobe segmentation algorithm for COPD patients. The method enhances fissures, removes unlikely fissure candidates, after which a B-spline is fitted iteratively through the remaining candidate objects. The iterative fitting approach circumvents the need to classify each object as being part of the fissure or being noise, and allows the fissure to be detected in multiple disconnected parts. This property is beneficial for good performance in patient data, containing incomplete and disease-affected fissures. The proposed algorithm is tested on 22 COPD patients, resulting in accurate lobe-based densitometry, and a median overlap of the fissure (defined 3 voxels wide) with an expert ground truth of 0.65, 0.54 and 0.44 for the three main fissures. This compares to complete lobe overlaps of 0.99, 0.98, 0.98, 0.97 and 0.87 for the five main lobes, showing promise for lobe segmentation on data of patients with moderate to severe COPD.
Year
DOI
Venue
2012
10.1117/12.910869
Proceedings of SPIE
Keywords
Field
DocType
lobes segmentation,B-spline fitting,COPD
Voxel,B-spline,COPD,Computer vision,Lung,Segmentation,Lobe,Ground truth,Artificial intelligence,Fissure,Physics
Conference
Volume
Issue
ISSN
8314
null
0277-786X
Citations 
PageRank 
References 
3
0.39
7
Authors
7
Name
Order
Citations
PageRank
Denis Shamonin1664.47
Marius Staring297159.25
m e bakker350.81
Changyan Xiao4985.01
Jan Stolk5332.95
Johan H. C. Reiber61767286.53
Berend C Stoel719911.58