Paper Info
Title
Interactive graph cut segmentation of touching neuronal structures from electron micrographs
Abstract
A novel interactive segmentation framework comprising of a two stage s-t mincut is proposed. The framework has been designed keeping in mind the need to segment touching neuronal structures in Electron Micrograph (EM) images. The first stage undersegments the image, and groups touching structures into a single class. The second stage accepts user interaction to separate touching structures. The technique introduces user feedback through a Markov Random Field formulation. Furthermore, a method for constructing interaction potentials using an edge response function is proposed. Encouraging results, and a comparison to state of the art methods is presented.
Year
DOI
Venue
2010
10.1109/ICIP.2010.5652042
Image Processing
Keywords
Field
DocType
Markov processes,edge detection,graph theory,image segmentation,medical image processing,neurophysiology,random processes,EM image,Markov random field formulation,edge response function,electron micrograph image,interactive graph cut segmentation,touching neuronal structure,two stage s-t mincut,Graph Cuts,Interactive Segmentation,Markov Random Fields
Graph theory,Cut,Computer vision,Markov process,Pattern recognition,Computer science,Segmentation,Markov random field,Edge detection,Image segmentation,Pixel,Artificial intelligence
Conference
ISSN
ISBN
Citations 
1522-4880 E-ISBN : 978-1-4244-7993-1
978-1-4244-7993-1
2
PageRank 
References 
Authors
0.37
5
2
Name
Order
Citations
PageRank
Vignesh Jagadeesh121712.74
B. S. Manjunath27561783.37