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© Research
Publication : Journal of structural biology

Segmentation of electron tomographic data sets using fuzzy set theory principles.

Scientific Fields
Diseases
Organisms
Applications
Technique

Published in Journal of structural biology - 01 Jun 2008

Garduño E, Wong-Barnum M, Volkmann N, Ellisman MH,

Link to Pubmed [PMID] – 18358741

Link to DOI – 10.1016/j.jsb.2008.01.017

J Struct Biol 2008 Jun; 162(3): 368-79

In electron tomography the reconstructed density function is typically corrupted by noise and artifacts. Under those conditions, separating the meaningful regions of the reconstructed density function is not trivial. Despite development efforts that specifically target electron tomography manual segmentation continues to be the preferred method. Based on previous good experiences using a segmentation based on fuzzy logic principles (fuzzy segmentation) where the reconstructed density functions also have low signal-to-noise ratio, we applied it to electron tomographic reconstructions. We demonstrate the usefulness of the fuzzy segmentation algorithm evaluating it within the limits of segmenting electron tomograms of selectively stained, plastic embedded spiny dendrites. The results produced by the fuzzy segmentation algorithm within the framework presented are encouraging.

https://pubmed.ncbi.nlm.nih.gov/18358741