Dynamic Recognition and Tracking of Barium Flow Field Based on Deglutition Video
Dynamic fluoroscopy was used to study swallowing in 84 adult patients. We proposed a method to extract the barium contrast region by improved interframe difference method, and to indirectly determine the position of epigmatous cartilage and cricopharyngeal muscle according to the location of barium meal. The method is easy to understand, and the extraction effect is good, with 85% probability of successful extraction. On the other hand, in order to evaluate the degree of deglutition difficulty, we used calculation to evaluate variables including displacement, duration, residual quantity, etc., except that there were gender differences in variables and external factors, such as illumination, most of the measurement variables had very good reliability. The experimental results showed that the moving target fluid barium was extracted by quantifying dynamic fluorescence deglutition and using gaussian based background subtraction algorithm. We conclude that this approach significantly reduces the time it takes clinicians to examine moving images. This paper describes how to study swallowing disorders by X-ray barium fluoroscopy, explains the application of interframe difference algorithm and background subtraction in deglutiography, and extracts the residual amounts in three locations: oral cavity, epiglottic cartilage and piriform fosse.
Martin-Harris B, Jones B. The Videofluorographic Swallowing Study [J]. Physical Medicine and Rehabilitation Clinics of North America, 2008, 19(4):769–785.
Kim SM, McCulloch TM, Rim K. Pharyngeal pressure analysis by the finite element method during liquid bolus swallow [J]. Ann Otol Rhinol Laryngol, 2000, 109:585–589.
McConnel FM. Analysis of pressure generation and bolus transit during pharyngeal swallowing [J]. Laryngoscope, 1988, 98:71–78.
Cook IJ. Normal and disordered swallowing: new insights [J]. Baillieres Clin Gastroenterol, 1991, 5:245–267.
Shengli Li. Rehabilitative evaluation and treatments for patient with multiple sclerosis [J]. Chinese Journal of rehabilitation Technology and Practice, 1998(4):178–181.
Palmer, J.B., Kuhlemeier, K.V., Tippett, D.C., Lynch, C. A protocol for the videofluorographic swallowing study. Dysphagia 1993, 8, 209–214.
Ertekin, C., Aydogdu, I. Neurophysiology of swallowing. Clin. Neurophysiol. 2003, 114, 2226–2244.
Yangwei Chen, Luodan Xu. Effect of early nasal feeding intervention on dysphagia complicated with pulmonary infection in stroke patients [J]. Jilin medicine, 2014, 35(15):3357.
Tjaden K. Speech and swallowing in Parkinson’s disease [J]. Topics in geriatric rehabilitation, 2008, 24(2):115.
Mosselman MJ, Kruitwagen CL, Schuurmans MJ, et al. Malnutrition and risk of malnutrition in patients with stroke: prevalence during hospital stay [J]. J Neurosci Nurs, 2013, 45(4):194–204.
Ekberg O, Feinberg MJ. Altered swallowing function in elderly patients without dysphagia: radiologic findings in 56 cases [J]. AJR. American journal of roentgenology, 1991, 156(6):1181–1184.
Dodds WJ, Man KM, Cook IJ, et al. Influence of bolus volume on swallow-induced hyoid movement in normal subjects [J]. American Journal of Roentgenology, 1988, 150(6):1307–1309.
Cook IJ, Dodds WJ, Dantas RO, et al. Opening mechanisms of the human upper esophageal sphincter [J]. American Journal of Physiology-Gastrointestinal and Liver Physiology, 1989, 257(5): G748–G759.
Dengel G, Robbins JA, Rosenbek JC. Image processing in swallowing and speech research [J]. Dysphagia, 1991, 6(1):30–39.
Lee JT, Park E, Jung TD. Automatic detection of the pharyngeal phase in raw videos for the videofluoroscopic swallowing study using efficient data collection and 3d convolutional networks [J]. Sensors, 2019, 19(18):3873.
Zulin Dou, Yue Lan, Fang Yu, et al. Application of videofluoroscopy digital analysis in swallowing function assessment for brainstem stroke patients with dysphagia [J]. Chinese Journal of Rehabilitation Medicine, 2013, 28(9):799–805.
Dantas RO, Dodds WJ, Massey BT, et al. The effect of high- vs low-density barium preparations on the quantitative features of swallowing [J]. American Journal of Roentgenology, 1989, 153(6):1191–1195.
Hsiao YT, Chuang CL, Jiang JA, et al. A contour based image segmentation algorithm using morphological edge detection [C]//2005 IEEE International Conference on systems, man and cybernetics. IEEE, 2005, 3:2962–2967.
Canny J. A computational approach to edge detection [J]. IEEE Transactions on pattern analysis and machine intelligence, 1986 (6):679–698.
Weng M, Huang G, Da X. A new interframe difference algorithm for moving target detection [C]//2010 3rd international congress on image and signal processing. IEEE, 2010, 1:285–289.
He Zhang. Research on moving object detection algorithm [D]. Wuhan: Wuhan University of Science and Technology, 2011.
Van Droogenbroeck M, Barnich O. ViBe: A disruptive method for background subtraction [J]. Background modeling and foreground detection for video surveillance, 2014:7.1–7.23.
Barnich O, Van Droogenbroeck M. ViBe: A universal background subtraction algorithm for video sequences [J]. IEEE Transactions on Image processing, 2010, 20(6):1709–1724.
Van Droogenbroeck M, Paquot O. Background subtraction: Experiments and improvements for ViBe [C]//2012 IEEE computer society conference on computer vision and pattern recognition workshops. IEEE, 2012:32–37.
Barnich O, Van Droogenbroeck M. ViBe: a powerful random technique to estimate the background in video sequences [C]//2009 IEEE international conference on acoustics, speech and signal processing. IEEE, 2009:945–948.
López-Rubio FJ, López-Rubio E. Local color transformation analysis for sudden illumination change detection [J]. Image and Vision Computing, 2015, 37:31–47.
Farnebäck G. Two-frame motion estimation based on polynomial expansion [C]//Scandinavian conference on Image analysis. Springer, Berlin, Heidelberg, 2003:363–370.
Wilhelm P, Reinhardt JM, Van Daele D. A Deep Learning Approach to Video Fluoroscopic Swallowing Exam Classification [C]//2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). IEEE, 2020:1647–1650.
Mildenberger P, Eichelberg M, Martin E. Introduction to the DICOM standard [J]. European radiology, 2002, 12(4):920–927.