Fast global interactive volume segmentation with regional supervoxel descriptors

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Fast global interactive volume segmentation with regional supervoxel descriptors

In this paper we propose a novel approach towards fast multi-class volume segmentation that exploits supervoxels in order to reduce complexity, time and memory requirements. Current methods for biomedical image segmentation typically require either complex mathematical models with slow convergence,...

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Bibliographic Details
Main Authors:	Luengo, Imanol, Basham, Mark, French, Andrew P.
Format:	Conference or Workshop Item
Published:	2016
Subjects:	Volume Interactive segmentation Random Forest Contextual Information Markov Random Fields
Online Access:	https://eprints.nottingham.ac.uk/34250/

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