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ProViz: a tool for explorative 3-D visualization and template matching in electron tomograms
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2016 (English)In: Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, ISSN 2168-1163Article in journal (Refereed) Epub ahead of print
Abstract [en]

Visual understanding is a key aspect when studying electron tomography data-sets, aside quantitative assessments such as registration of high-resolution structures. We here present the free software tool ProViz (Protein Visualization) for visualisation and template matching in electron tomograms of biological samples. The ProViz software contains methods and tools which we have developed, adapted and computationally optimised for easy and intuitive visualisation and analysis of electron tomograms with low signal-to-noise ratio. ProViz complements existing software in the application field and serves as an easy and convenient tool for a first assessment and screening of the tomograms. It provides enhancements in three areas: (1) improved visualisation that makes connections as well as intensity differences between and within objects or structures easier to see and interpret, (2) interactive transfer function editing with direct visual result feedback using both piecewise linear functions and Gaussian function elements, (3) computationally optimised template matching and tools to visually assess and interactively explore the correlation results. The visualisation capabilities and features of ProViz are demonstrated on various biological volume data-sets: bacterial filament structures in vitro, a desmosome and the transmembrane cadherin connections therein in situ, and liposomes filled with doxorubicin in solution. The explorative template matching is demonstrated on a synthetic IgG data-set.

Place, publisher, year, edition, pages
2016.
Keyword [en]
Electron tomography, direct volume rendering, image registration, connected component filtering, visualisation and analysis software
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:umu:diva-134331DOI: 10.1080/21681163.2016.1154483OAI: oai:DiVA.org:umu-134331DiVA: diva2:1092195
Available from: 2017-05-01 Created: 2017-05-01 Last updated: 2017-05-08

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Sandblad, Linda
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Department of Molecular Biology (Faculty of Medicine)
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CiteExportLink to record
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Citation style
  • apa
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  • de-DE
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