標題: AUTOMATIC IDENTIFYING LARYNGOPHARYNGEAL REFLUX USING ARTIFICIAL NEURAL NETWORK
作者: Lin, Sheng-Fuu
Chen, Hsien-Tse
Tsai, Tung-Lung
電機工程學系
Department of Electrical and Computer Engineering
關鍵字: Laryngopharyngeal Reflux;Feature extraction;Image processing;Artificial neural network
公開日期: 1-Feb-2012
摘要: Laryngopharyngeal Reflux mostly leads to burns of the pharynx and larynx by reflux from gastric acid and also leads to different degrees of burns in the esophagus and the stomach. This paper aims to develop a technique for analyzing pharyngeal and laryngeal images. With techniques of digital image processing, this paper can choose the suitable images from burns of the pharynx and larynx to obtain the feature zones of burns of the pharynx and larynx. Artificial neural network helps physicians to develop the diagnostic standard about the burns severity of Laryngopharyngeal Reflux. This paper divides the types of the complications into three degrees and compares with other ways (Hanson et al.(5) and Ilgner et al.(6)). The results can be the technical assistance in helping physicians to diagnose the severity of Laryngopharyngeal Reflux and to make a more precise diagnosis.
URI: http://dx.doi.org/10.1142/S1016237212002949
http://hdl.handle.net/11536/15845
ISSN: 1016-2372
DOI: 10.1142/S1016237212002949
期刊: BIOMEDICAL ENGINEERING-APPLICATIONS BASIS COMMUNICATIONS
Volume: 24
Issue: 1
起始頁: 47
結束頁: 56
Appears in Collections:Articles