title: Abnormal Image Detection in Endoscopy Videos Using a Filter Bank and Local Binary Patterns.
abstract: Finding mucosal abnormalities (e.g., erythema, blood, ulcer, erosion, and polyp) is one of the most essential tasks during endoscopy video review. Since these abnormalities typically appear in a small number of frames (around 5% of the total frame number), automated detection of frames with an abnormality can save physician's time significantly. In this paper, we propose a new multi-texture analysis method that effectively discerns images showing mucosal abnormalities from the ones without any abnormality since most abnormalities in endoscopy images have textures that are clearly distinguishable from normal textures using an advanced image texture analysis method. The method uses a "texton histogram" of an image block as features. The histogram captures the distribution of different "textons" representing various textures in an endoscopy image. The textons are representative response vectors of an application of a combination of Leung and Malik (LM) filter bank (i.e., a set of image filters) and a set of Local Binary Patterns on the image. Our experimental results indicate that the proposed method achieves 92% recall and 91.8% specificity on wireless capsule endoscopy (WCE) images and 91% recall and 90.8% specificity on colonoscopy images.
authors.affiliation: Department of Computer Science and Engineering, University of North Texas, Denton, TX 76203, U.S.A.
authors.forename: Ruwan
authors.initials: R
authors.lastname: Nawarathna
authors.affiliation: Department of Computer Science and Engineering, University of North Texas, Denton, TX 76203, U.S.A.
authors.forename: JungHwan
authors.initials: J
authors.lastname: Oh
authors.affiliation: Department of Computer Science and Engineering, University of North Texas, Denton, TX 76203, U.S.A.
authors.forename: Jayantha
authors.initials: J
authors.lastname: Muthukudage
authors.affiliation: Computer Science Department, Iowa State University, Ames, IA 50011, U.S.A.
authors.forename: Wallapak
authors.initials: W
authors.lastname: Tavanapong
authors.affiliation: Computer Science Department, Iowa State University, Ames, IA 50011, U.S.A.
authors.forename: Johnny
authors.initials: J
authors.lastname: Wong
authors.affiliation: Mayo Clinic College of Medicine, Rochester, MN 55905, U.S.A.
authors.forename: Piet C
authors.initials: PC
authors.lastname: de Groen
authors.affiliation: University of Mississippi Medical Center, Jackson, MS 39216, U.S.A.
authors.forename: Shou Jiang
authors.initials: SJ
authors.lastname: Tang
keywords: Colonoscopy; Filter bank; Local binary pattern; Texton; Texton dictionary; Wireless capsule endoscopy