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Matthias Schlachter, Tobias Fechter, Miro Jurisic

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    We developed a new visualization tool to help doctors assess deformable image registration (DIR) accuracy in radiotherapy. This method aids in identifying registration errors, improving treatment planning and image-guided adaptive radiotherapy.

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    Area of Science:

    • Medical Imaging
    • Radiotherapy
    • Computational Anatomy

    Background:

    • Deformable image registration (DIR) offers significant potential for advancing radiotherapy, including improved volume definition, treatment planning, and image-guided adaptive radiotherapy.
    • Accurate measurement of DIR is crucial for clinical integration but challenging without a known ground truth.
    • Visual assessment is a vital step for the clinical acceptance of DIR techniques.

    Purpose of the Study:

    • To propose and evaluate a novel visualization framework designed to facilitate the exploration and assessment of DIR accuracy.
    • To simplify the visual assessment process for radiation oncologists by providing interactive features for exploring candidate regions.

    Main Methods:

    • A visualization framework was developed based on voxel-wise comparison of local image patches.
    • Dissimilarity measures were computed and visualized to indicate local registration accuracy.
    • An evaluation was conducted with three radiation oncologists using lung regions to assess the framework's viability.

    Main Results:

    • The visualization framework supports fast and intuitive investigation of DIR accuracy, effectively identifying small errors.
    • Regions rated as visually accurate by oncologists showed an average registration error of 1.8 mm, with a maximum single landmark error of 3.3 mm.
    • The framework demonstrated viability in assessing DIR accuracy in a clinical context.

    Conclusions:

    • The proposed visualization framework effectively supports the visual assessment of deformable image registration accuracy in radiotherapy.
    • This tool can aid radiation oncologists in evaluating registration quality, potentially leading to improved radiotherapy workflows.
    • The framework's ability to highlight local registration discrepancies is valuable for ensuring treatment precision.