title: Optimal multiresolution 3D level-set method for liver segmentation incorporating local curvature constraints.
abstract: Advanced liver surgery requires a precise pre-operative planning, where liver segmentation and remnant liver volume are key elements to avoid post-operative liver failure. In that context, level-set algorithms have achieved better results than others, especially with altered liver parenchyma or in cases with previous surgery. In order to improve functional liver parenchyma volume measurements, in this work we propose two strategies to enhance previous level-set algorithms: an optimal multi-resolution strategy with fine details correction and adaptive curvature, as well as an additional semiautomatic step imposing local curvature constraints. Results show more accurate segmentations, especially in elongated structures, detecting internal lesions and avoiding leakages to close structures.
authors.affiliation: Group of Biomedical Image Technologies, ETSIT, Universidad Politécnica de Madrid, Spain. daniel.jimenezc@die.upm.es
authors.forename: Daniel
authors.initials: D
authors.lastname: Jimenez-Carretero
authors.forename: Laura
authors.initials: L
authors.lastname: Fernandez-de-Manuel
authors.forename: Javier
authors.initials: J
authors.lastname: Pascau
authors.forename: Jose M
authors.initials: JM
authors.lastname: Tellado
authors.forename: Enrique
authors.initials: E
authors.lastname: Ramon
authors.forename: Manuel
authors.initials: M
authors.lastname: Desco
authors.forename: Andres
authors.initials: A
authors.lastname: Santos
authors.forename: Maria J
authors.initials: MJ
authors.lastname: Ledesma-Carbayo
mesh_terms: D000465:Algorithms; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008099:Liver / Q000000981:diagnostic imaging*; D011859:Radiography