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 language||English (US)|
|Title of host publication||2015 13th International Workshop on Content-Based Multimedia Indexing, CBMI 2015|
|Publisher||IEEE Computer Society|
|State||Published - Jul 9 2015|
|Event||13th International Workshop on Content-Based Multimedia Indexing, CBMI 2015 - Prague, Czech Republic|
Duration: Jun 10 2015 → Jun 12 2015
|Name||Proceedings - International Workshop on Content-Based Multimedia Indexing|
|Other||13th International Workshop on Content-Based Multimedia Indexing, CBMI 2015|
|Period||6/10/15 → 6/12/15|
Bibliographical notePublisher Copyright:
© 2015 IEEE.
- Image texture
- Local Binary Pattern
- Ulcerative colitis