BIROn - Birkbeck Institutional Research Online

    Multi-atlas based image selection with label image constraint

    Cao, Y. and Li, Xuelong and Yan, P. (2012) Multi-atlas based image selection with label image constraint. In: UNSPECIFIED (ed.) 11th International Conference on Machine Learning and Applications. Washington, USA: IEEE Computer Society, pp. 311-316. ISBN 9781467346511.

    Full text not available from this repository.

    Abstract

    Atlas selection plays an important role in multiatlas based image segmentation. In atlas selection methods, manifold learning based techniques have recently emerged as very promisingly. However, due to the complexity of anatomical structures in raw images, it is difficult to get accurate atlas selection results by measuring only the distance between raw images on the manifolds. In this paper, we tackle this problem by proposing a label image constrained atlas selection (LICAS) method to exploit the shape and size information of the regions to be segmented from the label images. Constrained by the label images, a new manifold projection method is developed to help uncover the intrinsic similarity between the regions of interest across images. Compared with other existing methods, the experimental results of segmentation on 60 Magnetic Resonance (MR) images showed that the selected atlases are closer to the target structure and more accurate segmentation can be obtained by using the proposed method.

    Metadata

    Item Type: Book Section
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Depositing User: Sarah Hall
    Date Deposited: 06 Jun 2013 15:52
    Last Modified: 09 Aug 2023 12:33
    URI: https://eprints.bbk.ac.uk/id/eprint/7332

    Statistics

    Activity Overview
    6 month trend
    0Downloads
    6 month trend
    203Hits

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item Edit/View Item