A context-aware delayed agglomeration framework for EM segmentation.

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arXiv. 2014 Jun 5;:arXiv:1406.1476 [cs.CV]

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A context-aware delayed agglomeration framework for EM segmentation. Scheffer LabFlyEM

Parag T, Chakraborty A, Plaza SM

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Abstract

This paper proposes a novel agglomerative framework for Electron Microscopy (EM) image (or volume) segmentation. For the overall segmentation methodology, we propose a context-aware algorithm that clusters the over-segmented regions of different sub-classes (representing different biological entities) in different stages. Furthermore, a delayed scheme for agglomerative clustering, which postpones the merge of newly formed bodies, is also proposed to generate a more confident boundary prediction. We report significant improvements in both segmentation accuracy and speed attained by the proposed approaches over existing standard methods on both 2D and 3D datasets.

PMID: 26018659 [PubMed - indexed for MEDLINE]

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A context-aware delayed agglomeration framework for EM segmentation.

Abstract

PMID: 26018659 [PubMed - indexed for MEDLINE]

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