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    This study introduces a new motion estimation method for grating-based X-ray dark-field imaging. This technique reduces artifacts in medical imaging, improving diagnostic accuracy for lung diseases.

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    Area of Science:

    • Medical Imaging
    • Biophysics
    • Radiography

    Background:

    • Grating-based X-ray phase-contrast and dark-field radiography show promise for medical imaging.
    • Investigating dark-field imaging for early diagnosis of human pulmonary diseases.
    • Scanning interferometers used in these studies have reduced mechanical stability, leading to image artifacts from vibrations.

    Purpose of the Study:

    • To develop a novel method for estimating motion in grating-based X-ray imaging setups.
    • To prevent image artifacts caused by vibrations in scanning interferometers.
    • To improve the reliability of dark-field imaging for pulmonary disease diagnosis.

    Main Methods:

    • A novel maximum likelihood method was developed for motion estimation.
    • The method is specifically tailored for scanning X-ray setups.
    • It does not require sample-free areas and accounts for motion during and between exposures.

    Main Results:

    • The proposed method effectively estimates motion in grating-based X-ray imaging.
    • Artifacts caused by vibrations were prevented.
    • The technique is applicable to scanning setups without sample-free regions.

    Conclusions:

    • The novel maximum likelihood method enhances the quality of grating-based X-ray dark-field images.
    • This advancement supports the use of dark-field imaging for early detection of lung diseases.
    • The method offers improved motion correction for scanning radiography systems.