Title
Segmental Active Contour Model Integrating Region Information for Medical Image Segmentation
Abstract
A segmental active contour model integrating region information is proposed. Different deformation schemes are used at two stages for segmenting the object correctly in image plain. At the first stage the contour of the model is divided into several segments hierarchically that deform respectively using affine transformation. After the contour is deformed to the approximate boundary of object, a fine match mechanism using statistical information of local region is adopted to make the contour fit the object's boundary exactly. The experimental results indicate that the proposed model is robust to local minima and able to search for concave objects.
Year
DOI
Venue
2004
10.1007/978-3-540-28626-4_16
LECTURE NOTES IN COMPUTER SCIENCE
Keywords
Field
DocType
affine transformation,active contour model,local minima
Affine transformation,Active contour model,Computer vision,Scale-space segmentation,Control point,Pattern recognition,Computer science,Segmentation-based object categorization,Image segmentation,Maxima and minima,Artificial intelligence,Deformation (mechanics)
Conference
Volume
ISSN
Citations 
3150
0302-9743
0
PageRank 
References 
Authors
0.34
8
2
Name
Order
Citations
PageRank
Xin Ran111.70
Feihu Qi234727.19