Abstract
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.
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Straehle, C.N., Köthe, U., Knott, G., Hamprecht, F.A. (2011). Carving: Scalable Interactive Segmentation of Neural Volume Electron Microscopy Images. In: Fichtinger, G., Martel, A., Peters, T. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011. MICCAI 2011. Lecture Notes in Computer Science, vol 6891. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23623-5_82
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DOI: https://doi.org/10.1007/978-3-642-23623-5_82
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