Paper Info
Title
Automatic Segmentation of Lung Areas Based on SNAKES and Extraction of Abnormal Areas
Abstract
Segmentation for lung areas from CT images is important tasks on understanding tissue construction, computing and extracting abnormal areas. Recently, many segmentation methods based on contour model are presented. SNAKES (active contour model), on the other hand, are used extensively in computer vision and image processing applications particularly to locate the object boundaries. In lung segmentation, SNAKES is used for extracting the detail of ROI. However, a completely automatic segmentation method is not yet published, since it needs some manual efforts for initial contouring and constructing the contour models. In this paper, we propose a segmentation method for lung areas based on SNAKES without considering any manual operations. Furthermore, abnormal area including ground-glass opacity or lung cancer is classified by voxel density on the CT slice set. Experiment is performed employing nine thorax CT image sets and satisfactory results are obtained. Obtained results are shown along with a discussion.
Year
DOI
Venue
2005
10.1109/ICTAI.2005.44
ICTAI
Keywords
Field
DocType
segmentation method,lung segmentation,lung cancer,contour model,lung area,active contour model,automatic segmentation method,abnormal area,ct image,ct slice set,abnormal areas,automatic segmentation,lung areas,image segmentation,respiratory system,feature extraction
Voxel,Active contour model,Computer vision,Scale-space segmentation,Pattern recognition,Computer science,Segmentation,Segmentation-based object categorization,Feature extraction,Image segmentation,Artificial intelligence,Contouring
Conference
ISSN
ISBN
Citations 
1082-3409
0-7695-2488-5
9
PageRank 
References 
Authors
0.65
2
7
Name
Order
Citations
PageRank
Yoshinori Itai1213.86
Hyoungseop Kim229336.05
Seiji Ishikawa334249.06
Shigehiko Katsuragawa417226.20
Takayuki Ishida55612.36
Katsumi Nakamura6215.31
Akiyoshi Yamamoto7153.46