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NeuroMorph: A Toolset for the Morphometric Analysis and Visualization of 3D Models Derived from Electron Microscopy Image Stacks

Jorstad, Anne ; Nigro, Biagio ; Cali, Corrado ; Wawrzyniak, Marta ; Fua, Pascal ; Knott, Graham

In: Neuroinformatics, 2015, vol. 13, no. 1, p. 83-92

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    Titre
    • NeuroMorph: A Toolset for the Morphometric Analysis and Visualization of 3D Models Derived from Electron Microscopy Image Stacks
    Auteur
    • Jorstad, Anne. Computer Vision Lab, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
    • Nigro, Biagio. Centre for Electron Microscopy, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
    • Cali, Corrado. Centre for Electron Microscopy, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
    • Wawrzyniak, Marta. International Institute of Molecular and Cell Biology, Warsaw, Poland
    • Fua, Pascal. Computer Vision Lab, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
    • Knott, Graham. Centre for Electron Microscopy, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
    Type de document
    • Postprint
    Langue
    • Inglese
    Publié dans
    • Neuroinformatics, 2015, vol. 13, no. 1, p. 83-92. Springer US; http://www.springer-ny.com
    Autre version électronique
    Identifiant OAI-PMH
    • oai:doc.rero.ch:331241
    Summary
    Serialelectron microscopy imaging is crucial for exploring the structure of cells and tissues. The development of block face scanning electron microscopy methods and their ability to capture large image stacks, some with near isotropic voxels, is proving particularly useful for the exploration of brain tissue. This has led to the creation of numerous algorithms and software for segmenting out different features from the image stacks. However, there are few tools available to view these results and make detailed morphometric analyses on all, or part, of these 3D models. We have addressed this issue by constructing a collection of software tools, called NeuroMorph, with which users can view the segmentation results, in conjunction with the original image stack, manipulate these objects in 3D, and make measurements of any region. This approach to collecting morphometric data provides a faster means of analysing the geometry of structures, such as dendritic spines and axonal boutons. This bridges the gap that currently exists between rapid reconstruction techniques, offered by computer vision research, and the need to collect measurements of shape and form from segmented structures that is currently done using manual segmentation methods.