A knowledge-based framework for robust segmentation of high-resolution impedance manometry catheters in video-fluoroscopy images - Takeaways - MDSpire

A knowledge-based framework for robust segmentation of high-resolution impedance manometry catheters in video-fluoroscopy images

  • By

  • Manuel Maria Loureiro da Rocha

  • Dionne S.Brandsma

  • Lisette van der Molen

  • Maarten J. A. van Alphen

  • Michiel W. M. van den Brekel

  • Françoise J. Siepel

  • April 4, 2026

  • 0 min

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  • 1

    Head and neck cancer is a prevalent malignancy that often leads to oropharyngeal dysphagia, significantly impacting patient quality of life.

  • 2

    Videofluoroscopic swallow study is the gold standard for diagnosing dysphagia, but its analysis is prone to inter-rater variability.

  • 3

    High-Resolution Impedance Manometry provides quantitative swallow assessments but requires manual delineation of manometric regions, complicating analysis.

  • 4

    Knowledge-based segmentation methods offer a low-data alternative to deep learning for catheter detection in fluoroscopy, addressing data limitations.

  • 5

    The proposed template-free algorithm aims to improve HRIM catheter localization in VFSS images, enhancing integration and reducing clinician workload.

Original Source(s)

A knowledge-based framework for robust segmentation of high-resolution impedance manometry catheters in video-fluoroscopy images

  • by Manuel Maria Loureiro da Rocha, Dionne S.Brandsma, Lisette van der Molen, Maarten J. A. van Alphen, Michiel W. M. van den Brekel, Françoise J. Siepel

  • April 4, 2026

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