Paper Info
Title
Coupled Parallel Snakes For Segmenting Healthy And Pathological Retinal Arteries In Adaptive Optics Images
Abstract
In this paper, we propose two important improvements of an existing approach for automatically segmenting the walls of retinal arteries of healthy/pathological subjects in adaptive optics images. We illustrate the limits of the previous approach and propose to (i) modify the pre-segmentation step, and (ii) embed additional information through coupling energy terms in the parallel active contour model. The interest of these new elements as well as the pre-segmentation step is then evaluated against manual segmentations. They improve the robustness against low contrasted walls and morphological deformations that occur along vessels in case of pathologies. Noticeably, this strategy permits to obtain a mean error of 13.4% compared to an inter-physicians error of 17%, for the wall thickness which is the most sensitive measure used. Additionally, this mean error is in the same range than for healthy subjects.
Year
DOI
Venue
2014
10.1007/978-3-319-11755-3_35
IMAGE ANALYSIS AND RECOGNITION, ICIAR 2014, PT II
Keywords
Field
DocType
Active contour model, Adaptive optics, Retina imaging
Active contour model,Computer vision,Coupling,Pattern recognition,Computer science,Mean squared error,Robustness (computer science),Artificial intelligence,Retinal,Adaptive optics
Conference
Volume
ISSN
Citations 
8815
0302-9743
2
PageRank 
References 
Authors
0.42
2
5
Name
Order
Citations
PageRank
N. Lermé161.15
Florence Rossant213315.22
Isabelle Bloch32123170.75
Michel Pâques4182.27
Edouard Koch530.79