Paper Info
Title
Segmenting the Subthalamic Nucleus Using Narrow Band Limited Variational Level Set Method.
Abstract
We describe a novel variational level set based method for delineating the sub thalamic nucleus (STN) region of human brains from magnetic resonance (MR) images. Based on the understanding of specific imaging characteristic of STN, we apply a narrow band limitation in the region-based energy function for localizing the STN from initial contour information provided by doctors. The validity of the algorithm was tested on practical Parkinson's Patients' T1-weighted magnetic resonance images. Comparing to traditional edge-based and global region-based level set methods, our method achieves more reliable segmentation results. Also, our method is insensitive to the initial contour placement, making it applicable in practical surgical navigations.
Year
DOI
Venue
2011
10.1109/ICIG.2011.31
ICIG
Keywords
Field
DocType
global region-based level set,practical surgical navigation,t1-weighted magnetic resonance image,narrow band limited variational,region-based energy function,magnetic resonance,novel variational level,initial contour information,practical parkinson,level set method,initial contour placement,human brain,level set,edge detection,active contour,surgery,mathematical model,image segmentation,magnetic resonance image
Computer vision,Pattern recognition,Computer science,Level set method,Segmentation,Level set,Image segmentation,Thalamic nucleus,Artificial intelligence,Narrow band,Subthalamic nucleus,Magnetic resonance imaging
Conference
Citations 
PageRank 
References 
0
0.34
6
Authors
6
Name
Order
Citations
PageRank
Cong Xia141.77
Jiansheng Chen227331.28
Chunhua Hu373.57
Guangda Su413320.68
Hong-Wei Hao535927.28
Yu Ma621.12