Literature DB >> 27858156

A Supporting Platform for Semi-Automatic Hyoid Bone Tracking and Parameter Extraction from Videofluoroscopic Images for the Diagnosis of Dysphagia Patients.

Jun Chang Lee1, Kyoung Won Nam1, Dong Pyo Jang1, Nam Jong Paik2, Ju Seok Ryu2, In Young Kim3.   

Abstract

Conventional kinematic analysis of videofluoroscopic (VF) swallowing image, most popular for dysphagia diagnosis, requires time-consuming and repetitive manual extraction of diagnostic information from multiple images representing one swallowing period, which results in a heavy work load for clinicians and excessive hospital visits for patients to receive counseling and prescriptions. In this study, a software platform was developed that can assist in the VF diagnosis of dysphagia by automatically extracting a two-dimensional moving trajectory of the hyoid bone as well as 11 temporal and kinematic parameters. Fifty VF swallowing videos containing both non-mandible-overlapped and mandible-overlapped cases from eight patients with dysphagia of various etiologies and 19 videos from ten healthy controls were utilized for performance verification. Percent errors of hyoid bone tracking were 1.7 ± 2.1% for non-overlapped images and 4.2 ± 4.8% for overlapped images. Correlation coefficients between manually extracted and automatically extracted moving trajectories of the hyoid bone were 0.986 ± 0.017 (X-axis) and 0.992 ± 0.006 (Y-axis) for non-overlapped images, and 0.988 ± 0.009 (X-axis) and 0.991 ± 0.006 (Y-axis) for overlapped images. Based on the experimental results, we believe that the proposed platform has the potential to improve the satisfaction of both clinicians and patients with dysphagia.

Entities:  

Keywords:  Deglutition; Deglutition disorders; Diagnosis; Dysphagia; Hyoid bone; Videofluoroscopic

Mesh:

Year:  2016        PMID: 27858156     DOI: 10.1007/s00455-016-9759-x

Source DB:  PubMed          Journal:  Dysphagia        ISSN: 0179-051X            Impact factor:   3.438


  30 in total

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Review 6.  Dysphagia after stroke: incidence, diagnosis, and pulmonary complications.

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7.  Two-dimensional perceptual videofluoroscopic swallowing analysis of the pharyngeal phase in patients older than 50 years.

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9.  A fuzzy logic diagnosis system for classification of pharyngeal dysphagia.

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10.  Inter-rater Reliability of Videofluoroscopic Dysphagia Scale.

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Journal:  Ann Rehabil Med       Date:  2012-12-28
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4.  Hyoid Bone Tracking in a Videofluoroscopic Swallowing Study Using a Deep-Learning-Based Segmentation Network.

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5.  Measurement of laryngeal elevation by automated segmentation using Mask R-CNN.

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