• Login
    View Item 
    •   Eurographics DL Home
    • Eurographics Workshops and Symposia
    • VCBM: Eurographics Workshop on Visual Computing for Biomedicine
    • VCBM 16: Eurographics Workshop on Visual Computing for Biology and Medicine
    • View Item
    •   Eurographics DL Home
    • Eurographics Workshops and Symposia
    • VCBM: Eurographics Workshop on Visual Computing for Biomedicine
    • VCBM 16: Eurographics Workshop on Visual Computing for Biology and Medicine
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    A Feasibility Study on Automated Protein Aggregate Characterization Utilizing a Hybrid Classification Model

    Thumbnail
    View/Open
    105-109.pdf (3.176Mb)
    Date
    2016
    Author
    Eschweiler, Dennis
    Gadermayr, Michael
    Unger, Jakob
    Nippold, Markus
    Falkenburger, Björn
    Merhof, Dorit
    Pay-Per-View via TIB Hannover:

    Try if this item/paper is available.

    Metadata
    Show full item record
    Abstract
    The characterization of cytoplasmic protein aggregates based on time-lapse fluorescence microscopy imaging data is important for research in neuro-degenerative diseases such as Parkinson. As the manual assessment is time-consuming and subject to significant variability, incentive for the development of an objective automated system is provided. We propose and evaluate a pipeline consisting of cell-segmentation, tracking and classification of neurological cells. Focus is specifically on the novel and challenging classification task which is covered by relying on feature extraction followed by a hybrid classification approach incorporating a support vector machine focusing on mainly stationary information and a hidden Markov model to incorporate temporal context. Several image representations are experimentally evaluated to identify cell properties that are important for discrimination. Relying on the proposed approach, classification accuracies up to 80 % are reached. By extensively analyzing the outcomes, we discuss about strengths and weaknesses of our method as a quantitative assessment tool.
    BibTeX
    @inproceedings {10.2312:vcbm.20161277,
    booktitle = {Eurographics Workshop on Visual Computing for Biology and Medicine},
    editor = {Stefan Bruckner and Bernhard Preim and Anna Vilanova and Helwig Hauser and Anja Hennemuth and Arvid Lundervold},
    title = {{A Feasibility Study on Automated Protein Aggregate Characterization Utilizing a Hybrid Classification Model}},
    author = {Eschweiler, Dennis and Gadermayr, Michael and Unger, Jakob and Nippold, Markus and Falkenburger, Björn and Merhof, Dorit},
    year = {2016},
    publisher = {The Eurographics Association},
    ISSN = {2070-5786},
    ISBN = {978-3-03868-010-9},
    DOI = {10.2312/vcbm.20161277}
    }
    URI
    http://dx.doi.org/10.2312/vcbm.20161277
    https://diglib.eg.org:443/handle/10.2312/vcbm20161277
    Collections
    • VCBM 16: Eurographics Workshop on Visual Computing for Biology and Medicine

    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA
     

     

    Browse

    All of Eurographics DLCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    BibTeX | TOC

    Create BibTeX Create Table of Contents

    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA