loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
2008 21st IEEE International Symposium on Computer-Based Medical Systems
Web-Based Multi-Observer Segmentation Evaluation Tool
June 17-June 19
ISBN: 978-0-7695-3165-6
ASCII Text
x 
 
Yaoyao Zhu, Xiaolei Huang, Daniel Lopresti, Rodeny Long, Sameer Antani, Zhiyun Xue, George Thoma, "Web-Based Multi-Observer Segmentation Evaluation Tool," Computer-Based Medical Systems, IEEE Symposium on, pp. 167-169, 2008 21st IEEE International Symposium on Computer-Based Medical Systems, 2008.
 
 
BibTex
x
 
@article{ 10.1109/CBMS.2008.121,
author = {Yaoyao Zhu and Xiaolei Huang and Daniel Lopresti and Rodeny Long and Sameer Antani and Zhiyun Xue and George Thoma},
title = {Web-Based Multi-Observer Segmentation Evaluation Tool},
journal ={Computer-Based Medical Systems, IEEE Symposium on},
volume = {0},
year = {2008},
issn = {1063-7125},
pages = {167-169},
doi = {http://doi.ieeecomputersociety.org/10.1109/CBMS.2008.121},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Computer-Based Medical Systems, IEEE Symposium on
TI - Web-Based Multi-Observer Segmentation Evaluation Tool
SN - 1063-7125
SP167
EP169
A1 - Yaoyao Zhu,
A1 - Xiaolei Huang,
A1 - Daniel Lopresti,
A1 - Rodeny Long,
A1 - Sameer Antani,
A1 - Zhiyun Xue,
A1 - George Thoma,
PY - 2008
KW - Segmentation
KW - Evaluation
KW - multiple-observer
VL - 0
JA - Computer-Based Medical Systems, IEEE Symposium on
ER -
 
Multi-observer segmentation evaluation is useful in the imaging community. We have developed web-based software for automatic performance evaluation of multiple image segmentations which is based on the Baysian Decision framework. It computes a probabilistic estimate of the true segmentation (ground truth map) and performance measures for the individual segmentations (sensitivity and specificity). The strength of the tool is that it integrates the two kinds of prior knowledge of segmentations: the truth prior (the prior probability) and the observer prior (the performance measures of observers), which can generate more accurate evaluations.
Index Terms:
Segmentation, Evaluation, multiple-observer
Citation:
Yaoyao Zhu, Xiaolei Huang, Daniel Lopresti, Rodeny Long, Sameer Antani, Zhiyun Xue, George Thoma, "Web-Based Multi-Observer Segmentation Evaluation Tool," cbms, pp.167-169, 2008 21st IEEE International Symposium on Computer-Based Medical Systems, 2008
Usage of this product signifies your acceptance of the Terms of Use.