Dynamic Recognition and Tracking of Barium Flow Field Based on Deglutition Video

Authors

  • Guofeng Qin Department of Computer Science and Technology, Tongji University, Shanghai, China
  • Jianhuang Zou Department of Computer Science and Technology, Tongji University, Shanghai, China
  • Qiufang Xia Shanghai first rehabilitation hospital, Shanghai, China
  • Jiahao Qin Department of Computer Science and Technology, Tongji University, Shanghai, China

DOI:

https://doi.org/10.13052/jwe1540-9589.20214

Keywords:

Dynamic fluoroscopy, X-ray barium fluoroscopy, swallowing disorders, interframe difference algorithm, background subtraction algorithm

Abstract

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.

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Author Biographies

Guofeng Qin, Department of Computer Science and Technology, Tongji University, Shanghai, China

Guofeng Qin is with The Department of Computer Science and Technology as associate Prof, Tongji University, Shanghai, 201804, China. Received BA form Hunan University in 1995, MA form Science and Technology of Huazhong University in 2001, and PHD from Tongji University in 2004. e-mail: gfqing@tongji.edu.cn.

Jianhuang Zou, Department of Computer Science and Technology, Tongji University, Shanghai, China

Jianhuang Zou is a graduate student in School of Electronics and Information Engineering at Tongji University, China. Received BA Fuzhou University e-mail: jianhuang_zou@tongji.edu.cn. Her research focuses on image recognition.

Qiufang Xia, Shanghai first rehabilitation hospital, Shanghai, China

Qiufang Xia is with the director and deputy chief physician of the Department of Chinese Medicine Rehabilitation at Shanghai First Rehabilitation Hospital, China Acupuncture and Moxibustion, Shanghai, 200092, China. Received BA from Anhui University of Traditional Chinese Medicine in 2001, MA from Shanghai University of Traditional Chinese Medicine in 2011. e-mail: 13651899419@163.com.

Jiahao Qin, Department of Computer Science and Technology, Tongji University, Shanghai, China

Jiahao Qin is a graduate student in School of Electronics and Information Engineering at Tongji University, China. e-mail: jiahao_qin@tongji.edu.cn. His research focuses on image recognition.

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Published

2021-03-20

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Section

Advanced Practice in Web Engineering