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Automatic cropping method of chest radiographs based on adaptive binarization.

Masataka Imura, Yoshito Tabata, Rikuta Ishigaki

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |October 11, 2013
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    Summary

    This study introduces an automated X-ray image cropping method using adaptive binarization to reduce manual workload for radiological technologists. The new technique streamlines the digital radiography workflow, enhancing patient care.

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    Area of Science:

    • Medical Imaging
    • Radiography Technology
    • Image Processing

    Background:

    • General radiography systems are essential for medical diagnosis, but fixed detector sizes create challenges with varying patient anatomy.
    • Digital X-ray imaging necessitates manual cropping of radiographs, diverting technologists' attention from patient care and measurement tasks.

    Purpose of the Study:

    • To develop an automated image processing method for cropping X-ray images.
    • To reduce the manual burden on radiological technologists in the general radiography workflow.

    Main Methods:

    • The study proposes an image processing method for automatic cropping of X-ray images.
    • Adaptive binarization is employed as a pre-processing step for radiographs.

    Main Results:

    • The proposed method was applied to chest radiographs.
    • Evaluation of the method by radiological technologists was conducted.

    Conclusions:

    • The developed image processing technique shows potential for automating X-ray image cropping.
    • This automation can significantly alleviate the workload of radiological technologists, improving workflow efficiency.