‘Multi-Atlas’

On the Application of Human Rater Models to Statistical Fusion in Multi-Atlas Labeling

Sep. 1, 2011—A. Asman, Antong Chen, and B. Landman. “On the Application of Human Rater Models to Statistical Fusion in Multi-Atlas Labeling.” In MICCAI 2011 Workshop on Multi-Atlas Methods and Statistical Fusion. Toronto, Canada, September 2011 (Oral Presentation) NIHMS317651 Full text: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.701.3272&rep=rep1&type=pdf Abstract Segmentation is critical to understanding the complex relationships between biological structure and function. Statistical algorithms...

Estimation of Registration Accuracy Applied to Multi-Atlas Segmentation

Sep. 1, 2011—R. Datteri, A. Asman, B. Landman, and B. Dawant. “Estimation of Registration Accuracy Applied to Multi-Atlas Segmentation.” In . Toronto, Canada, September 2011 (Oral Presentation) Full text: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.728.4212&rep=rep1&type=pdf Abstract Multi-atlas registration-based segmentation has recently become a popular technique in medical imaging. Since the quality of individual atlas segmentations affect the quality of the results, atlas selection...

The spatial quality variation exhibited by registered atlases. A representative slice from the true labels (manually drawn) of a target brain is presented in (A). Four example observations of this slice can be seen in (B). The quality of the observations seen in (B) is compared to the true labels seen in (A) to construct the spatial quality variation heat maps presented in (C). Note that the spatial variation is independent of the actual labels of the brain.

Characterizing Spatially Varying Performance to Improve Multi-Atlas Multi-Label Segmentation

Jul. 30, 2011—Andrew J. Asman and Bennett A. Landman. “Characterizing Spatially Varying Performance to Improve Multi-Atlas Multi-Label Segmentation”, In Proceedings of the 2011 International Conference on Information Processing in Medical Imaging (IPMI), Irsee, Bavaria, July 2011 (Oral presentation) (28% acceptance rate) PMC3140117 Full text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3140117/ Abstract Segmentation of medical images has become critical to building understanding of biological...