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Citation
Kriston-Vizi, J., Thong, N.W., Poh, C.L., Yee, K.C., Ling, J.S., Kraut, R., Wasser, M. (2011). Gebiss: an ImageJ plugin for the specification of ground truth and the performance evaluation of 3d segmentation algorithms.  BMC Bioinformatics 12(): 232.
FlyBase ID
FBrf0214312
Publication Type
Research paper
Abstract

Image segmentation is a crucial step in quantitative microscopy that helps to define regions of tissues, cells or subcellular compartments. Depending on the degree of user interactions, segmentation methods can be divided into manual, automated or semi-automated approaches. 3D image stacks usually require automated methods due to their large number of optical sections. However, certain applications benefit from manual or semi-automated approaches. Scenarios include the quantification of 3D images with poor signal-to-noise ratios or the generation of so-called ground truth segmentations that are used to evaluate the accuracy of automated segmentation methods.We have developed Gebiss; an ImageJ plugin for the interactive segmentation, visualisation and quantification of 3D microscopic image stacks. We integrated a variety of existing plugins for threshold-based segmentation and volume visualisation.We demonstrate the application of Gebiss to the segmentation of nuclei in live Drosophila embryos and the quantification of neurodegeneration in Drosophila larval brains. Gebiss was developed as a cross-platform ImageJ plugin and is freely available on the web at http://imaging.bii.a-star.edu.sg/projects/gebiss/.

PubMed ID
PubMed Central ID
PMC3225128 (PMC) (EuropePMC)
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    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    BMC Bioinformatics
    Title
    BMC Bioinformatics
    Publication Year
    2000-
    ISBN/ISSN
    1471-2105
    Data From Reference
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    Alleles (4)
    Genes (3)
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    Transgenic Constructs (1)