Paper Info
Title
Anchor point thinning using a skeleton based on the Euclidean distance transformation
Abstract
Thinning is one of the most frequently used methods to know the geometrical feature of objects. It also provides the topological feature and length measurements about an object. For example, the tree structure of the bronchus is determined by using the thinned result of it. This paper presents a three dimensional thinning method which can control the quality of result concerning appearance of spurious short branches by a parameter value.This method is constructed by integrating the anchor point thinning algorithm and the skeletonization algorithm based upon the Euclidean metric. We applied the proposed method to artificial figures and a three dimensional bronchus region extracted from a real chest X-ray CT image and confirmed that the proposed method could control the number of spike branches and shrinkage of branches.Dr. Toyofumi Saito, an associate professor who was one of the most active researchers in the field of image processing in Japan and a young leader of the author's laboratory, passed away on 26 October 2000. This paper describes one of his last works. We have lost a most reliable and most promising colleague, an experienced supervisor, and a very sincere friend. We would like to dedicate this paper to Dr. Toyofumi Saito and to all those who have shared and cherished the memories of him.
Year
DOI
Venue
2002
10.1109/ICPR.2002.1048186
Pattern Recognition, 2002. Proceedings. 16th International Conference  
Keywords
Field
DocType
computerised tomography,image thinning,lung,medical image processing,Euclidean distance transformation,anchor point thinning,branch shrinkage,bronchus,chest X-ray CT image,geometrical feature,length measurements,skeleton,skeletonization algorithm,spike branches,topological feature,tree structure
Computer vision,Thinning,Pattern recognition,Length measurement,Euclidean distance,Skeletonization,Artificial intelligence,Skeleton (computer programming),Spurious relationship,Mathematics,Thinning algorithm
Conference
Volume
ISSN
ISBN
3
1051-4651
0-7695-1695-X
Citations 
PageRank 
References 
5
0.54
5
Authors
2
Name
Order
Citations
PageRank
Yoshito Mekada111516.08
Jun-ichiro Toriwaki2578136.04