Show simple item record

dc.contributor.authorBereciartua, Arantza
dc.contributor.authorPicon, Artzai
dc.contributor.authorGaldran, Adrian
dc.contributor.authorIriondo, Pedro M.
dc.date.accessioned2016-10-25T09:10:36Z
dc.date.available2016-10-25T09:10:36Z
dc.date.issued2016-08
dc.identifier.citationComputer Methods and Programs in Biomedicine 2016 Aug; 132:149-160.en
dc.identifier.issn0169-2607en
dc.identifier.urihttp://hdl.handle.net/11556/306
dc.description.abstractBiopsies for diagnosis can sometimes be replaced by non-invasive techniques such as CT and MRI. Surgeons require accurate and efficient methods that allow proper segmentation of the organs in order to ensure the most reliable intervention planning. Automated liver segmentation is a difficult and open problem where CT has been more widely explored than MRI. MRI liver segmentation represents a challenge due to the presence of characteristic artifacts, such as partial volumes, noise and low contrast. In this paper, we present a novel method for multichannel MRI automatic liver segmentation. The proposed method consists of the minimization of a 3D active surface by means of the dual approach to the variational formulation of the underlying problem. This active surface evolves over a probability map that is based on a new compact descriptor comprising spatial and multisequence information which is further modeled by means of a liver statistical model. This proposed 3D active surface approach naturally integrates volumetric regularization in the statistical model. The advantages of the compact visual descriptor together with the proposed approach result in a fast and accurate 3D segmentation method. The method was tested on 18 healthy liver studies and results were compared to a gold standard made by expert radiologists. Comparisons with other state-of-the-art approaches are provided by means of nine well established quality metrics. The obtained results improve these methodologies, achieving a Dice Similarity Coefficient of 98.59.en
dc.description.sponsorshipHEPATOOL project - Spanish Department of Science and Innovation, IPT-2011-1514-900000en
dc.language.isoengen
dc.publisherELSEVIER IRELAND LTD, ELSEVIER HOUSE, BROOKVALE PLAZA, EAST PARK SHANNON, CO, CLARE, 00000, IRELANDen
dc.title3D Active Surfaces for Liver Segmentation in Multisequence MRI Imagesen
dc.typearticleen
dc.identifier.doi10.1016/j.cmpb.2016.04.028en
dc.isiYesen
dc.rights.accessRightsembargoedAccessen
dc.subject.keywordsMedical imagingen
dc.subject.keywords3D active contoursen
dc.subject.keywordsliver segmentationen
dc.subject.keywordsactive surfaceen
dc.subject.keywordsmagnetic resonance imagingen
dc.subject.keywordsvariational techniquesen
dc.subject.keywordsmultichannelen
dc.subject.keywordsmultivariate image descriptorsen


Files in this item

Thumbnail

    Show simple item record