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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," 2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS), 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 ={2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS)}, 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 - 2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS) 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 - 2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS) ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CBMS.2008.121
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
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