Automatic Segmentation and Detection of Small Bowel Angioectasias in WCE Images

  • Pedro M. VieiraEmail author
  • Catarina P. Silva
  • Dalila Costa
  • Ismael F. Vaz
  • Carla Rolanda
  • Carlos S. Lima


Angioectasias are lesions that occur in the blood vessels of the bowel and are the cause of more than 8% of all gastrointestinal bleeding episodes. They are usually classified as bleeding related lesions, however current state-of-the-art bleeding detection algorithms present low sensitivity in the detection of these lesions. This paper proposes a methodology for the automatic detection of angioectasias in wireless capsule endoscopy (WCE) videos. This method relies on the automatic selection of a region of interest, selected by using an image segmentation module based on the Maximum a Posteriori (MAP) approach where a new accelerated version of the Expectation-Maximization (EM) algorithm is also proposed. Spatial context information is modeled in the prior probability density function by using Markov Random Fields with the inclusion of a weighted boundary function. Higher order statistics computed in the CIELab color space with the luminance component removed and intensity normalization of high reflectance regions, showed to be effective features regarding angioectasia detection. The proposed method outperforms some current state of the art algorithms, achieving sensitivity and specificity values of more than 96% in a database containing 800 WCE frames labeled by two gastroenterologists.


Capsule endoscopy EM segmentation Machine learning Markov Random Fields Angioectasias 



This work is supported by FCT (Fundação para a Ciência e Tecnologia) with the reference Project UID/EEA/04436/2019 and with the PhD Grant SFRH/BD/92143/2013.


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Copyright information

© Biomedical Engineering Society 2019

Authors and Affiliations

  1. 1.CMEMS-Uminho Research UnitUniversity of MinhoGuimarãesPortugal
  2. 2.Algoritmi CenterUniversity of MinhoGuimaraesPortugal
  3. 3.Life and Health Sciences Research InstituteUniversity of MinhoBragaPortugal
  4. 4.ICVS/3Bś - PT Government Associate LaboratoryBraga/GuimarãesPortugal
  5. 5.Department of GastroenterologyHospital de BragaBragaPortugal

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