Title :
Web-Based Multi-Observer Segmentation Evaluation Tool
Author :
Zhu, Yaoyao ; Huang, Xiaolei ; Lopresti, Daniel ; Long, Rodeny ; Antani, Sameer ; Xue, Zhiyun ; Thoma, George
Author_Institution :
Dept. of Comput. Sci. & Eng., Lehigh Univ., Bethlehem, PA
Abstract :
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.
Keywords :
Bayes methods; Internet; image segmentation; probability; Baysian decision framework; Web-based software; multiple image segmentation; probabilistic estimate; Bayesian methods; Biomedical engineering; Biomedical imaging; Computer science; Decision theory; Image segmentation; Sensitivity and specificity; Software libraries; Software performance; USA Councils; Evaluation; Segmentation; multiple-observer;
Conference_Titel :
Computer-Based Medical Systems, 2008. CBMS '08. 21st IEEE International Symposium on
Conference_Location :
Jyvaskyla
Print_ISBN :
978-0-7695-3165-6
DOI :
10.1109/CBMS.2008.121