Abstract
A fast fully automatic method of segmenting the prostate from 3D MR scans is presented, incorporating dynamic multi-atlas label fusion. The diffeomorphic demons method is used for non-rigid registration and a comparison of alternate metrics for atlas selection is presented. A comparison of results from an average shape atlas and the multi-atlas approach is provided. Using the same clinical dataset and manual contours from 50 clinical scans as Klein et al. (2008) a median Dice similarity coefficient of 0.86 was achieved with an average surface error of 2.00mm using the multi-atlas segmentation method. © 2011 Springer-Verlag.
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CITATION STYLE
Dowling, J. A., Fripp, J., Chandra, S., Pluim, J. P. W., Lambert, J., Parker, J., … Salvado, O. (2011). Fast automatic multi-atlas segmentation of the prostate from 3D MR images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6963 LNCS, pp. 10–21). https://doi.org/10.1007/978-3-642-23944-1_2
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