Paper Info
Title
Segmentation Of Connective Tissue In The Optic Nerve Head Using An Anisotropic Markov Random Field
Abstract
The study of the biomechanical response of the optic nerve head (ONH) to different levels of intraocular pressure (IOP) is key in understanding the mechanisms that underlie the development and progression of glaucoma. Our goal is to study this behavior using the finite element method on serial sections of normal and glaucomatous monkey ONHs. Segmentation of the beam-like connective tissue of the ONH is particularly challenging due to the artifacts introduced in the acquisition procedure. We present a new algorithm for segmentation of beam-like structures, based on the Expectation-Maximization (EM) method. The main difference with previous EM-based segmentation algorithms is that we employ an anisotropic Markov Random Field, which incorporates preferred directions based on the underlying image structure and coherence. Results on synthetic and ONH images show the ability of the algorithm to accurately segment these structures in presence of significant artifacts, and suggest its suitability to other medical imaging segmentation tasks.
Year
DOI
Venue
2004
10.1109/ISBI.2004.1398482
2004 2ND IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: MACRO TO NANO, VOLS 1 and 2
Keywords
Field
DocType
head,expectation maximization,markov processes,anisotropic magnetoresistance,biomedical imaging,connective tissue,geometrical optics,biomechanics,finite element analysis,finite element method,irrigation,neurophysiology,finite element methods,image segmentation
Computer vision,Glaucoma,Markov process,Pattern recognition,Neurophysiology,Markov random field,Computer science,Medical imaging,Segmentation,Image segmentation,Artificial intelligence,Optic nerve
Conference
Citations 
PageRank 
References 
1
0.34
6
Authors
3
Name
Order
Citations
PageRank
Vicente Grau13812.23
J. Crawford Downs281.82
Claude Burgoyne370.86