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    SHREC 2021: Classification in Cryo-electron Tomograms (Unknown language)

    In: Eurographics Workshop on 3D Object Retrieval ; 5-17  ; 2021

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    Cryo-electron tomography (cryo-ET) is an imaging technique that allows three-dimensional visualization of macro-molecular assemblies under near-native conditions. Cryo-ET comes with a number of challenges, mainly low signal-to-noise and inability to obtain images from all angles. Computational methods are key to analyze cryo-electron tomograms. To promote innovation in computational methods, we generate a novel simulated dataset to benchmark different methods of localization and classification of biological macromolecules in tomograms. Our publicly available dataset contains ten tomographic reconstructions of simulated cell-like volumes. Each volume contains twelve different types of complexes, varying in size, function and structure. In this paper, we have evaluated seven different methods of finding and classifying proteins. Seven research groups present results obtained with learning-based methods and trained on the simulated dataset, as well as a baseline template matching (TM), a traditional method widely used in cryo-ET research. We show that learning-based approaches can achieve notably better localization and classification performance than TM. We also experimentally confirm that there is a negative relationship between particle size and performance for all methods.

    Table of contents conference proceedings

    The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.

    1
    Shape Classification of Building Information Models using Neural Networks
    Evangelou, Iordanis / Vitsas, Nick / Papaioannou, Georgios / Georgioudakis, Manolis / Chatzisymeon, Apostolos et al. | 2021
    5
    SHREC 2021: Classification in Cryo-electron Tomograms
    Gubins, Ilja / Chaillet, Marten L. / Schot, Gijs van der / Trueba, M. Cristina / Veltkamp, Remco C. / Förster, Friedrich / Wang, Xiao / Kihara, Daisuke / Moebel, Emmanuel / Nguyen, Nguyen P. et al. | 2021
    19
    SHREC 2021: Surface-based Protein Domains Retrieval
    Langenfeld, Florent / Aderinwale, Tunde / Christoffer, Charles / Shin, Woong-Hee / Terashi, Genki / Wang, Xiao / Kihara, Daisuke / Benhabiles, Halim / Hammoudi, Karim / Cabani, Adnane et al. | 2021

    How to get this title?

    Check access
    Download
    Commercial Copyright fee: €14.50 Basic fee: €4.00 Total price: €18.50
    Academic Copyright fee: €4.50 Basic fee: €2.00 Total price: €6.50

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