Please use this identifier to cite or link to this item:

TitleSegmentation of angiodysplasia lesions in WCE images using a MAP approach with Markov random fields
Author(s)Vieira, Pedro Miguel
Gonçalves, Bruno
Rolanda, Carla
Lima, C. S.
Issue date2016
JournalIEEE Engineering in Medicine and Biology Society Conference Proceedings
Abstract(s)This paper deals with the segmentation of angiodysplasias in wireless capsule endoscopy images. These lesions are the cause of almost 10% of all gastrointestinal bleeding episodes, and its detection using the available software presents low sensitivity. This work proposes an automatic selection of a ROI using an image segmentation module based on the MAP approach where an accelerated version of the EM algorithm is used to iteratively estimate the model parameters. Spatial context is modeled in the prior probability density function using Markov Random Fields. The color space used was CIELab, specially the a component, which highlighted most these type of lesions.The proposed method is the first regarding this specific type of lesions, but when compared to other state-of-the-art segmentation methods, it almost doubles the results.
TypeConference paper
AccessRestricted access (UMinho)
Appears in Collections:DEI - Artigos em atas de congressos internacionais

Files in This Item:
File Description SizeFormat 
  Restricted access
771,34 kBAdobe PDFView/Open

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID