Fully automatic, completely reliable segmentation in medical images is an unrealistic expectation with today's technology. However, many automatic segmentation algorithms may achieve a near-correct solution, incorrect only in a small region. For these situations, an interactive editing tool is required, ideally in 3D, that is usually left to a manual correction. We formulate the editing task as an energy minimization problem that may be solved with a modified version of either graph cuts or the random walker 3D segmentation algorithms. Both algorithms employ a seeded user interface, that may be used in this scenario for a user to seed erroneous voxels as belonging to the foreground or the background. In our formulation, it is unnecessary for the user to specify both foreground and background seeds. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Grady, L., & Funka-Lea, G. (2006). An energy minimization approach to the data driven editing of presegmented images/volumes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4191 LNCS-II, pp. 888–895). Springer Verlag. https://doi.org/10.1007/11866763_109
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