has a user interface that enables medical experts to load and
view local images and multiple experts¨ segmentations. The
software is based on Bayesian Decision Rule.
users to submit the segmentations to the server with the initial
associated specificity and sensibility. The server
computes and sends back to the users with
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). It can
handle four different scenarios with differing application
purposes: (1) with known truth prior; (2) with observer prior;
(3) with neither truth prior nor observer prior; and (4) with
both truth prior and observer prior.
We developed the software in Java. This software is a tool as part of study of the evolution
of lesions related to cervical cancer conducted by NCI together
with the National Library of Medicine (NLM).