October, 2011

The inaccuracies of the STAPLE model of rater behavior. A representative slice from the truth model is shown in (A). The expected STAPLE model of rater behavior can be seen in (B). STAPLE operates under the assumption that there is a uniform probability that any given rater would mis-label a given voxel. The observed model of rater behavior can be seen in (C). The primary difference between (B) and (C) is that the human raters showed a clear inclination to mislabel boundary pixels and other ambiguous regions.

Robust Statistical Label Fusion through Consensus Level, Labeler Accuracy and Truth Estimation (COLLATE)

Oct. 31, 2011—Andrew J. Asman and Bennett A. Landman. “Robust Statistical Label Fusion through Consensus Level, Labeler Accuracy and Truth Estimation (COLLATE)”, IEEE Transactions on Medical Imaging. 2011 October; 30(10): 1779–1794. PMC3150602 † Full text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3150602/ Abstract Segmentation and delineation of structures of interest in medical images is paramount to quantifying and characterizing structural, morphological, and functional...