Using image processing technology combined with decision tree algorithm in laryngeal video stroboscope automatic identification of common vocal fold diseases

Chung Feng Jeffrey Kuo, Po Chun Wang, Yueng Hsiang Chu, Hsing Won Wang, Chun Yu Lai

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

This study used the actual laryngeal video stroboscope videos taken by physicians in clinical practice as the samples for experimental analysis. The samples were dynamic vocal fold videos. Image processing technology was used to automatically capture the image of the largest glottal area from the video to obtain the physiological data of the vocal folds. In this study, an automatic vocal fold disease identification system was designed, which can obtain the physiological parameters for normal vocal folds, vocal paralysis and vocal nodules from image processing according to the pathological features. The decision tree algorithm was used as the classifier of the vocal fold diseases. The identification rate was 92.6%, and the identification rate with an image recognition improvement processing procedure after classification can be improved to 98.7%. Hence, the proposed system has value in clinical practices.

Original languageEnglish
Pages (from-to)228-236
Number of pages9
JournalComputer Methods and Programs in Biomedicine
Volume112
Issue number1
DOIs
Publication statusPublished - Oct 2013

Fingerprint

Stroboscopes
Decision Trees
Vocal Cords
Decision trees
Image processing
Technology
Image recognition
Identification (control systems)
Classifiers
Processing
Paralysis
Physicians

Keywords

  • Decision tree
  • Glottal area
  • Laryngeal video stroboscope
  • Vocal fold diseases

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Health Informatics

Cite this

Using image processing technology combined with decision tree algorithm in laryngeal video stroboscope automatic identification of common vocal fold diseases. / Jeffrey Kuo, Chung Feng; Wang, Po Chun; Chu, Yueng Hsiang; Wang, Hsing Won; Lai, Chun Yu.

In: Computer Methods and Programs in Biomedicine, Vol. 112, No. 1, 10.2013, p. 228-236.

Research output: Contribution to journalArticle

@article{28b173c0fccb494c88deccd2f3383ad2,
title = "Using image processing technology combined with decision tree algorithm in laryngeal video stroboscope automatic identification of common vocal fold diseases",
abstract = "This study used the actual laryngeal video stroboscope videos taken by physicians in clinical practice as the samples for experimental analysis. The samples were dynamic vocal fold videos. Image processing technology was used to automatically capture the image of the largest glottal area from the video to obtain the physiological data of the vocal folds. In this study, an automatic vocal fold disease identification system was designed, which can obtain the physiological parameters for normal vocal folds, vocal paralysis and vocal nodules from image processing according to the pathological features. The decision tree algorithm was used as the classifier of the vocal fold diseases. The identification rate was 92.6{\%}, and the identification rate with an image recognition improvement processing procedure after classification can be improved to 98.7{\%}. Hence, the proposed system has value in clinical practices.",
keywords = "Decision tree, Glottal area, Laryngeal video stroboscope, Vocal fold diseases",
author = "{Jeffrey Kuo}, {Chung Feng} and Wang, {Po Chun} and Chu, {Yueng Hsiang} and Wang, {Hsing Won} and Lai, {Chun Yu}",
year = "2013",
month = "10",
doi = "10.1016/j.cmpb.2013.06.021",
language = "English",
volume = "112",
pages = "228--236",
journal = "Computer Methods and Programs in Biomedicine",
issn = "0169-2607",
publisher = "Elsevier Ireland Ltd",
number = "1",

}

TY - JOUR

T1 - Using image processing technology combined with decision tree algorithm in laryngeal video stroboscope automatic identification of common vocal fold diseases

AU - Jeffrey Kuo, Chung Feng

AU - Wang, Po Chun

AU - Chu, Yueng Hsiang

AU - Wang, Hsing Won

AU - Lai, Chun Yu

PY - 2013/10

Y1 - 2013/10

N2 - This study used the actual laryngeal video stroboscope videos taken by physicians in clinical practice as the samples for experimental analysis. The samples were dynamic vocal fold videos. Image processing technology was used to automatically capture the image of the largest glottal area from the video to obtain the physiological data of the vocal folds. In this study, an automatic vocal fold disease identification system was designed, which can obtain the physiological parameters for normal vocal folds, vocal paralysis and vocal nodules from image processing according to the pathological features. The decision tree algorithm was used as the classifier of the vocal fold diseases. The identification rate was 92.6%, and the identification rate with an image recognition improvement processing procedure after classification can be improved to 98.7%. Hence, the proposed system has value in clinical practices.

AB - This study used the actual laryngeal video stroboscope videos taken by physicians in clinical practice as the samples for experimental analysis. The samples were dynamic vocal fold videos. Image processing technology was used to automatically capture the image of the largest glottal area from the video to obtain the physiological data of the vocal folds. In this study, an automatic vocal fold disease identification system was designed, which can obtain the physiological parameters for normal vocal folds, vocal paralysis and vocal nodules from image processing according to the pathological features. The decision tree algorithm was used as the classifier of the vocal fold diseases. The identification rate was 92.6%, and the identification rate with an image recognition improvement processing procedure after classification can be improved to 98.7%. Hence, the proposed system has value in clinical practices.

KW - Decision tree

KW - Glottal area

KW - Laryngeal video stroboscope

KW - Vocal fold diseases

UR - http://www.scopus.com/inward/record.url?scp=84883811247&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84883811247&partnerID=8YFLogxK

U2 - 10.1016/j.cmpb.2013.06.021

DO - 10.1016/j.cmpb.2013.06.021

M3 - Article

C2 - 23915804

AN - SCOPUS:84883811247

VL - 112

SP - 228

EP - 236

JO - Computer Methods and Programs in Biomedicine

JF - Computer Methods and Programs in Biomedicine

SN - 0169-2607

IS - 1

ER -