Parallel programming of gradient-based iterative image reconstruction schemes for optical tomography

Andreas H. Hielscher, Sebastian Bartel

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Optical tomography (OT) is a fast developing novel imaging modality that uses near-infrared (NIR) light to obtain cross-sectional views of optical properties inside the human body. A major challenge remains the time-consuming, computational-intensive image reconstruction problem that converts NIR transmission measurements into cross-sectional images. To increase the speed of iterative image reconstruction schemes that are commonly applied for OT, we have developed and implemented several parallel algorithms on a cluster of workstations. Static process distribution as well as dynamic load balancing schemes suitable for heterogeneous clusters and varying machine performances are introduced and tested. The resulting algorithms are shown to accelerate the reconstruction process to various degrees, substantially reducing the computation times for clinically relevant problems.

    Original languageEnglish (US)
    Pages (from-to)101-113
    Number of pages13
    JournalComputer Methods and Programs in Biomedicine
    Volume73
    Issue number2
    DOIs
    StatePublished - Feb 2004

    Keywords

    • Heterogeneous cluster
    • Near-infrared (NIR)
    • Optical tomography
    • Parallel computing

    ASJC Scopus subject areas

    • Software
    • Computer Science Applications
    • Health Informatics

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