Change detection and classification in brain MR images using Change Vector Analysis

Rita Lopes Simoes, Cornelis H. Slump

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    4 Citations (Scopus)

    Abstract

    The automatic detection of longitudinal changes in brain images is valuable in the assessment of disease evolution and treatment efficacy. Most existing change detection methods that are currently used in clinical research to monitor patients suffering from neurodegenerative diseases—such as Alzheimer’s—focus on large-scale brain deformations. However, such patients often have other brain impairments, such as infarcts, white matter lesions and hemorrhages, which are typically overlooked by the deformation-based methods. Other unsupervised change detection algorithms have been proposed to detect tissue intensity changes. The outcome of these methods is typically a binary change map, which identifies changed brain regions. However, understanding what types of changes these regions underwent is likely to provide equally important information about lesion evolution. In this paper, we present an unsupervised 3D change detection method based on Change Vector Analysis. We compute and automatically threshold the Generalized Likelihood Ratio map to obtain a binary change map. Subsequently, we perform histogram-based clustering to classify the change vectors. We obtain a Kappa Index of 0.82 using various types of simulated lesions. The classification error is 2%. Finally, we are able to detect and discriminate both small changes and ventricle expansions in datasets from Mild Cognitive Impairment patients.
    Original languageUndefined
    Title of host publication33rd Annual International Conference of the IEEE EMBS 2011
    Place of PublicationUSA
    PublisherIEEE Engineering in Medicine and Biology Society
    Pages7803-7807
    Number of pages5
    ISBN (Print)978-1-4244-4122-8
    DOIs
    Publication statusPublished - 2011
    Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2011 - Boston Marriott Copley Place Hotel, Boston, United States
    Duration: 30 Aug 20113 Sep 2011
    Conference number: 33

    Publication series

    Name
    PublisherIEEE Engineering in Medicine & Biology Society

    Conference

    Conference33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2011
    Abbreviated titleEMBC
    CountryUnited States
    CityBoston
    Period30/08/113/09/11

    Keywords

    • IR-78930
    • EWI-20596
    • METIS-281536

    Cite this

    Lopes Simoes, R., & Slump, C. H. (2011). Change detection and classification in brain MR images using Change Vector Analysis. In 33rd Annual International Conference of the IEEE EMBS 2011 (pp. 7803-7807). USA: IEEE Engineering in Medicine and Biology Society. https://doi.org/10.1109/IEMBS.2011.6091923