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Tracking a Swallowed Object in Esophagus Ultrasonic Tomographic Animation for Diagnosis of Dysphagia

Published: 11 August 2020 Publication History

Abstract

Herein, we propose a quantitative method to evaluate swallowing ability. In Japan, where the population is aging, the number of patients with aspiration pneumonia will increase in the future. Methods to quantitatively assess swallowing ability are currently not being developed, and some doctors make decisions based on x-rays, endoscopes, and water drinking tests. These methods are invasive to the patient and the amount of information obtained is insufficient. The purpose of this study is to quantitatively evaluate the swallowing ability by photographing the state of swallowing food with an ultrasonic diagnostic device and processing the images. Muscle and food in the images were separated using filters, labeling, and single regression analysis. Swallowing ability was assessed quantitatively using optical flow.

References

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N. Takahashi, T. Kikutani, F. Tamura, et al.: "Videoendoscopic assessment of swallowing function to predict the future incidence of pneumonia of the elderly", Journal of Oral Rehabilitation, Vol. 39, No. 6, pp. 429--437 (2012)
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A. Tokifuji, Y. Matsushima, K. Hachisuka, et al.: "Texture, sensory and swallowing characteristics of high-pressure-heat-treated pork meat gel as a dysphagia diet", Meat Science, Vol. 93, No. 4, pp. 843--848 (2013)
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  1. Tracking a Swallowed Object in Esophagus Ultrasonic Tomographic Animation for Diagnosis of Dysphagia

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    ICCMS '20: Proceedings of the 12th International Conference on Computer Modeling and Simulation
    June 2020
    219 pages
    ISBN:9781450377034
    DOI:10.1145/3408066
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    • Central Queensland University
    • DUT: Dalian University of Technology
    • University of Wollongong, Australia
    • Swinburne University of Technology
    • University of Technology Sydney
    • National Tsing Hua University: National Tsing Hua University

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 11 August 2020

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    Author Tags

    1. Medical image
    2. Object recognition
    3. Real-time monitoring
    4. Small intestine
    5. Ultrasound image
    6. Video recognition
    7. food design

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