A context-aware delayed agglomeration framework for EM segmentation.

janelia7_blocks-janelia7_biblio_header | block
arXiv. 2014 Jun 5;:arXiv:1406.1476 [cs.CV]
View Article on
A context-aware delayed agglomeration framework for EM segmentation. Scheffer LabFlyEM
Parag T, Chakraborty A, Plaza SM
PDF of article
janelia7_blocks-janelia7_biblio_abstract | block

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]

node:body | entity_field

Full text of article

janelia7_blocks-janelia7_biblio_authors | block

Janelia Authors

janelia7_blocks-janelia7_biblio_tools | block