Compensation of breathing motion artifacts in thoracic pet images by wavelet-based deconvolution

Issam El Naqa, Daniel A. Low, Jeffrey D. Bradley, Milos Vicic, Joseph O. Deasy

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

    3 Scopus citations

    Abstract

    In biological imaging of thoracic tumors using FDG-PET, blurring due to breathing motion often significantly degrades the quality of the observed image, which then obscures the tumor boundary. The effect could be detrimental in small lesions. We demonstrate a deconvolution technique that combines patient-specific motion estimates of tissue trajectories with wavelet decomposition to compensate for breathing-motion induced artifacts. The lung motion estimates were obtained using a breathing model that maps spatial trajectories in CT data as a function of tidal volume and airflow measured by spirometry. Initial results showed good improvement in the spatial resolution, especially in the direction of major lung motion (craniocaudal) on phantom data as well as on clinical data with large or small tumors.

    Original languageEnglish
    Title of host publication2006 3rd IEEE International Symposium on Biomedical Imaging
    Subtitle of host publicationFrom Nano to Macro - Proceedings
    Pages980-983
    Number of pages4
    StatePublished - Nov 17 2006
    Event2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Arlington, VA, United States
    Duration: Apr 6 2006Apr 9 2006

    Publication series

    Name2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings
    Volume2006

    Conference

    Conference2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro
    Country/TerritoryUnited States
    CityArlington, VA
    Period04/6/0604/9/06

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