A portable measuring system for cross-sectional ultrasound images using spatial compounding and edge sharpening

Masayoshi Tsubai, Kiyotaka Fukumoto, Osamu Fukuda, Satoshi Muraki, Naohiro Ueno

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Citations (Scopus)

    Abstract

    This paper proposes a compensation for a blurred image caused by misregistration in spatial compounding. The edge sharpening based on morphological operations is applied to the compounded image. A portable measuring system of a cross-sectional ultrasound image is designed for measuring body composition. The system is developed for non-medical applications, for example, measurement of the volume of muscle and subcutaneous fat in lower extremities, upper extremities and abdomen for health care and sports science. A number of partially overlapping images that have been obtained from multiple angles are combined into a single compounded image. In experiment on human abdomen, the image quality was improved in speckle suppression and edge enhancement by using ensemble averaging and morphological edge sharpening. Resulting wide fleld-of-view image was sufficiently deblurred without emphasizing noise.

    Original languageEnglish
    Title of host publication29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
    Pages2150-2154
    Number of pages5
    DOIs
    Publication statusPublished - 2007
    Event29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07 - Lyon, France
    Duration: Aug 23 2007Aug 26 2007

    Publication series

    NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
    ISSN (Print)0589-1019

    Other

    Other29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
    Country/TerritoryFrance
    CityLyon
    Period8/23/078/26/07

    All Science Journal Classification (ASJC) codes

    • Signal Processing
    • Biomedical Engineering
    • Computer Vision and Pattern Recognition
    • Health Informatics

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