Semi-automatic tracking, smoothing and segmentation of hyoid bone motion from videofluoroscopic swallowing study

Kim, Won‐Seok; Zeng, Pengcheng; Shi, Jianghong; Lee, Youngjo; Paik, Nam–Jong

doi:10.1371/journal.pone.0188684

Cited by 11 publications

(12 citation statements)

References 34 publications

(41 reference statements)

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“…However, manual process may accompany with measurement errors as well as inter-and intra-rater variations [12]. It can also be time-consuming and labor-intensive especially in cases with prolonged swallowing duration or high frame rates [7]. These factors have led to limited application of swallowing kinematic analysis in clinical practice.…”

Section: Related Workmentioning

confidence: 99%

“…Quantitative kinematic analysis for swallowing difficulty is carried out based on the VFSS images containing information of the anatomic and dynamic properties of swallowing [5,6]. Unfortunately, the swallowing kinematic analysis demands labor-intensive and time-consuming processes for the manual marking of the swallowing structures, hence limiting its clinical utility and applicability [7].…”

Section: Introductionmentioning

confidence: 99%

“…Previously, various methods have been proposed to automatically track the swallowing structures such as the hyoid bone for kinematic analysis through image processing and machine learning algorithms. These algorithms include sobel edge detection [7,8] and active shape matching [9], Haar classifier matching [10] and local binary patterns in the image processing, and recently, convolutional neural networks (CNN) in machine learning [11]. However, in these previously proposed methods, manual corrections of the swallowing kinematic analyses was still required because tracking the hyoid bone is frequently failed when the image contrast is abruptly changed in the duration of passing through the mandible.…”

Section: Introductionmentioning

confidence: 99%

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Online Learning for the Hyoid Bone Tracking During Swallowing With Neck Movement Adjustment Using Semantic Segmentation

Lee

Seo

et al. 2020

IEEE Access

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Swallowing difficulty is a major health concern of the elderly population. The gold standard examination to assess swallowing function is videofluoroscopic swallowing study (VFSS). Hyoid kinematic parameters extracted from VFSS images can be quantitative indicators of swallowing difficulty. In previous studies, its tracking failures are still not resolved when passing through the mandible. Furthermore, it is difficult to be applied in kinematic analysis because the hyoid trajectories can be susceptible to irrelevant neck movements during swallowing. The aim of this study is to develop a robust algorithm for obtaining high-accuracy trajectories of the hyoid bone during swallowing with adjustment of the neck movements. We propose a CNN-based hyoid tracking algorithm which consists of single-domain networks for hyoid tracking and an attention U-Net with conditional random fields for semantic segmentation of the hyoid bone and the cervical vertebrae. The results show that the proposed method can track the hyoid bone robustly compared to the previous methods as measured by a success plot of one-pass evaluation. In addition, the proposed semantic segmentation method achieved the highest dice coefficient for the hyoid bone and the cervical vertebrae. Finally, the obtained hyoid trajectories were evaluated by a root mean squared error, relative error of range of motion, and Pearson's correlation analysis. The proposed algorithm can provide ability to automatically analyze the hyoid motions during swallowing in clinical practice and will potentially enable physician's decision making on diagnostic and therapeutic modalities based on quantitative swallowing assessments.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Online Learning for the Hyoid Bone Tracking During Swallowing With Neck Movement Adjustment Using Semantic Segmentation

Lee

Seo

et al. 2020

IEEE Access

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“…Kim et al . developed software which can track, smooth and segment the hyoid bone motion from VFSS 20 .…”

Section: Introductionmentioning

confidence: 99%

Automatic hyoid bone detection in fluoroscopic images using deep learning

Zhang

Coyle

Sejdić

2018

Sci Rep

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The displacement of the hyoid bone is one of the key components evaluated in the swallow study, as its motion during swallowing is related to overall swallowing integrity. In daily research settings, experts visually detect the hyoid bone in the video frames and manually plot hyoid bone position frame by frame. This study aims to develop an automatic method to localize the location of the hyoid bone in the video sequence. To automatically detect the location of the hyoid bone in a frame, we proposed a single shot multibox detector, a deep convolutional neural network, which is employed to detect and classify the location of the hyoid bone. We also evaluated the performance of two other state-of-art detection methods for comparison. The experimental results clearly showed that the single shot multibox detector can detect the hyoid bone with an average precision of 89.14% and outperform other auto-detection algorithms. We conclude that this automatic hyoid bone tracking system is accurate enough to be widely applied as a pre-processing step for image processing in dysphagia research, as well as a promising development that may be useful in the diagnosis of dysphagia.

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“…Finally, the latest works on hyoid bone kinematics put forward as more pertinent [28] the measurements of the hyoid bone motion peak. Semi-automatic measurement techniques are being developed [29] to encourage the use of these parameters in the future.…”

Section: Discussionmentioning

confidence: 99%

How a personalised transportable folding device for seating impacts dysphagia

Woisard

Costes

Colineaux³

et al. 2019

Eur Arch Otorhinolaryngol

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Purpose A personalised transportable folding device for seating (DATP) on a standard seat was developed by an occupational therapist at the Toulouse University Hospital Centre (patent no. WO 2011121249 A1) based on the hypothesis that the use of a seat to assist with better positioning on any chair during meals modifies the sitting posture and has an impact on cervical statics which increases the amplitude of movements of the axial skeleton (larynx and hyoid bone) and benefits swallowing. The aim of this work is to demonstrate that an improvement in sitting posture with the help of the DATP, through Hyoid bone motion, has an impact on the quality of swallowing in a dysphagic population which benefits from the device in comparison to a dysphagic population which does not benefit from the device after 1 month of care. The secondary endpoints concern the evaluation of the impact on other characteristics of swallowing, posture, the acceptability of the device and the quality of life. Methodology This is a randomised comparative clinical trial. The blind was not possible for the patients but the examiner who evaluated the outcome criterion was blinded to the group to which the patient belonged. The outcome criterion was the measurement of the hyoid bone movement during swallowing. The other criteria were collected during the videofluoroscopic examination of swallowing and by use of a questionnaire. Fifty-six (56) patients were included: 30 in the group without device (D−) and 26 in the group with the device (D+). All the patients benefited from a training course on seating. Only the D+ patients participated in this course where the use of the device was explained and the device was then kept for use at home for 1 month. Results A significant improvement was noted in the postural criteria before and after use, in favour of a better posture for the two groups (p < 0.001) and more hyoid bone motion in the D+ group. The difference was significant in the bivariate analysis for horizontal movement (p = 0.04). After adjustment of potential factors of confusion, we noted a significant mean difference for the three distances in the D+ group in comparison to the D− group, of + 0.33 (95% CI [+ 0.17; + 0.48]) for horizontal movement, + 0.22 (95% CI [+ 0.03; + 0.40]) for vertical movement and + 0.37 (95% CI = [+ 0.20; + 0.53]) for horizontal movement. However, the other parameters, and notably the other swallowing markers were not significantly modified by the use of the device. Conclusion The personalised transportable folding device for seating developed to reduce dysphagia has an action on hyoid bone motion during swallowing. However, this positive effect on an intermediate outcome criterion of the quality of swallowing was not associated with an improvement in swallowing efficiency in the study population. The diversity of diseases with which the patients in this study were afflicted is a factor to be controlled in future studies with this device.

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Semi-automatic tracking, smoothing and segmentation of hyoid bone motion from videofluoroscopic swallowing study

Cited by 11 publications

References 34 publications

Online Learning for the Hyoid Bone Tracking During Swallowing With Neck Movement Adjustment Using Semantic Segmentation

Online Learning for the Hyoid Bone Tracking During Swallowing With Neck Movement Adjustment Using Semantic Segmentation

Automatic hyoid bone detection in fluoroscopic images using deep learning

How a personalised transportable folding device for seating impacts dysphagia

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