Interactive segmentation algorithms should respond within seconds and require minimal user guidance. This is a challenge on 3D neural electron microscopy images. We propose a supervoxel-based energy function with a novel background prior that achieves these goals. This is verified by extensive experiments with a robot mimicking human interactions. A graphical user interface offering access to an open source implementation of these algorithms is made available. © 2011 Springer-Verlag.
CITATION STYLE
Straehle, C. N., Köthe, U., Knott, G., & Hamprecht, F. A. (2011). Carving: Scalable interactive segmentation of neural volume electron microscopy images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6891 LNCS, pp. 653–660). https://doi.org/10.1007/978-3-642-23623-5_82
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