Detection of ulcerative colitis severity in colonoscopy video frames

Ashok Dahal, Junghwan Oh, Wallapak Tavanapong, Johnny Wong, Piet C. De Groen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Ulcerative colitis (UC) is a chronic inflammatory disease characterized by periods of relapses and remissions affecting more than 500,000 people in the United States. The therapeutic goals of UC are to first induce and then maintain disease remission. However, it is very difficult to evaluate the severity of UC objectively because of non-uniform nature of symptoms associated with UC, and large variations in their patterns. To address this, we objectively measure and classify the severity of UC presented in optical colonoscopy video frames based on the image textures. To extract distinct textures, we are using a hybrid approach in which a new proposed feature based on the accumulation of pixel value differences is combined with an existing feature such as LBP (Local Binary Pattern). The experimental results show the hybrid method can achieve more than 90% overall accuracy.

Original languageEnglish (US)
Title of host publication2015 13th International Workshop on Content-Based Multimedia Indexing, CBMI 2015
PublisherIEEE Computer Society
ISBN (Electronic)9781467368704
DOIs
StatePublished - Jul 9 2015
Event13th International Workshop on Content-Based Multimedia Indexing, CBMI 2015 - Prague, Czech Republic
Duration: Jun 10 2015Jun 12 2015

Publication series

NameProceedings - International Workshop on Content-Based Multimedia Indexing
Volume2015-July
ISSN (Print)1949-3991

Other

Other13th International Workshop on Content-Based Multimedia Indexing, CBMI 2015
CountryCzech Republic
CityPrague
Period6/10/156/12/15

Keywords

  • Image texture
  • Local Binary Pattern
  • Severity
  • Ulcerative colitis

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