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Abnormal Image Detection in Endoscopy Videos Using a Filter Bank and Local Binary Patterns.

Ruwan Nawarathna1, JungHwan Oh1, Jayantha Muthukudage1

  • 1Department of Computer Science and Engineering, University of North Texas, Denton, TX 76203, U.S.A.

Neurocomputing
|August 19, 2014
PubMed
Summary

This study introduces a novel multi-texture analysis for detecting mucosal abnormalities in endoscopy videos. The method accurately identifies abnormal frames, significantly aiding physicians in reviewing wireless capsule endoscopy (WCE) and colonoscopy images.

Keywords:
ColonoscopyFilter bankLocal binary patternTextonTexton dictionaryWireless capsule endoscopy

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Area of Science:

  • Medical Imaging
  • Computer Vision
  • Gastroenterology

Background:

  • Automated detection of mucosal abnormalities in endoscopy is crucial for efficient physician review.
  • Abnormalities like erythema, blood, ulcers, erosions, and polyps appear in a small fraction of frames.
  • Advanced image texture analysis can distinguish abnormal from normal mucosal textures.

Purpose of the Study:

  • To develop and evaluate a new multi-texture analysis method for automated detection of mucosal abnormalities in endoscopic images.
  • To improve the efficiency of endoscopy video review by identifying abnormal frames.

Main Methods:

  • The proposed method utilizes a "texton histogram" derived from image blocks as features.
  • Textons are generated using a combination of Leung and Malik (LM) filter bank and Local Binary Patterns.
  • This approach analyzes the distribution of various textures within endoscopy images.

Main Results:

  • The method achieved 92% recall and 91.8% specificity on wireless capsule endoscopy (WCE) images.
  • It also demonstrated high performance on colonoscopy images, with 91% recall and 90.8% specificity.
  • Experimental results confirm the effectiveness of the multi-texture analysis in discerning abnormalities.

Conclusions:

  • The proposed multi-texture analysis method is effective for detecting mucosal abnormalities in endoscopic imaging.
  • This technique offers a significant time-saving tool for physicians during endoscopy video review.
  • The method shows high accuracy and specificity in both WCE and colonoscopy applications.