Autor segons l'article: Akram, F.; Soomro, S.; Munir, A.; Lee, C.H.; Choi, K.N.
Departament: Enginyeria Informàtica i Matemàtiques
Autor/s de la URV: AKRAM , FARHAN; Soomro, S.; Munir, A.; Lee, C.H.; Choi, K.N.
Paraules clau: endocardium epicardium heart right ventricle
Resum: Segmentation of left and right ventricles plays a crucial role in quantitatively analyzing the global and regional information in the cardiac magnetic resonance imaging (MRI). In MRI, the intensity inhomogeneity and weak or blurred object boundaries are the problems, which makes it difficult for the intensity-based segmentation methods to properly delineate the regions of interests (ROI). In this paper, a hybrid signed pressure force function (SPF) is proposed, which yields both local and global image fitted differences in an additive fashion. A characteristic term is also introduced in the SPF function to restrict the contour within the ROI. The overlapping dice index and Hausdorff-Distance metrics have been used over cardiac datasets for quantitative validation. Using 2009 LV MICCAI validation dataset, the proposed method yields DSC values of 0.95 and 0.97 for endocardial and epicardial contours, respectively. Using 2012 RVMICCAI dataset, for the endocardial region, the proposed method yields DSC values of 0.97 and 0.90 and HD values of 8.51 and 7.67 for ED and ES, respectively. For the epicardial region, it yields DSC values of 0.92 and 0.91 and HD values of 6.47 and 9.34 for ED and ES, respectively. Results show its robustness in the segmentation application of the cardiac MRI. Universitat Rovira i Virgili
Grup de recerca: Robòtica i Visió Intel.ligents
Àrees temàtiques: Enginyeria informàtica Ingeniería informática Computer engineering
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 1748-670X
Identificador de l'autor: 0000-0003-4109-2645; ; ; ;
Pàgina final: num. 8350680
Volum de revista: 2017
Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
Enllaç font original: https://www.hindawi.com/journals/cmmm/2017/8350680/
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
DOI de l'article: 10.1155/2017/8350680
Entitat: http://nportal0.urv.cat:18080/fourrepo/rest/digitalobjects/DS?objectId=PC%3A3100&datastreamId=DocumentPrincipal&mime=application%2Fpdf
Any de publicació de la revista: 2017
Pàgina inicial: Art
Tipus de publicació: Article Artículo Article
Repositori URV