Abstract
Optical colonoscopy is the preferred method for colon cancer screening and prevention. The goal of colonoscopy is to find and remove colonic polyps, precursors to colon cancer. However, colonoscopy is not a perfect procedure. Recent clinical studies report a significant polyp miss due to insufficient quality of colonoscopy. To complicate the problem, the existing guidelines for a “good” colonoscopy, such as maintaining a minimum withdrawal time of 6 min, are not adequate to guarantee the quality of colonoscopy. In response to this problem, this paper presents a method that can objectively measure the quality of an examination by assessing the informativeness of the corresponding colonoscopy images. By assigning a normalized quality score to each colonoscopy frame, our method can detect the onset of a hasty examination and encourage a more diligent procedure. The computed scores can also be averaged and reported as the overall quality of colonoscopy for quality monitoring purposes. Our experiments reveal that the suggested method achieves higher sensitivity and specificity to non-informative frames than the existing image quality assessment methods for colonoscopy videos.
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This research has been supported by an ASU-Mayo Clinic research grant.
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Tajbakhsh, N., Chi, C., Sharma, H., Wu, Q., Gurudu, S.R., Liang, J. (2014). Automatic Assessment of Image Informativeness in Colonoscopy. In: Yoshida, H., Näppi, J., Saini, S. (eds) Abdominal Imaging. Computational and Clinical Applications. ABD-MICCAI 2014. Lecture Notes in Computer Science(), vol 8676. Springer, Cham. https://doi.org/10.1007/978-3-319-13692-9_14
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DOI: https://doi.org/10.1007/978-3-319-13692-9_14
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