title   
  

Disjunctive normal shape models

Warning The system is temporarily closed to updates for reporting purpose.

Ramesh, Nisha and Mesadi, Fitsum and Çetin, Müjdat and Taşdizen, Tolga (2015) Disjunctive normal shape models. In: 12th International Symposium on Biomedical Imaging (ISBI 2015), New York, NY

This is the latest version of this item.

[img]PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
411Kb

Official URL: http://dx.doi.org/ 10.1109/ISBI.2015.7164170

Abstract

A novel implicit parametric shape model is proposed for segmentation and analysis of medical images. Functions representing the shape of an object can be approximated as a union of N polytopes. Each polytope is obtained by the intersection of M half-spaces. The shape function can be approximated as a disjunction of conjunctions, using the disjunctive normal form. The shape model is initialized using seed points defined by the user. We define a cost function based on the Chan-Vese energy functional. The model is differentiable, hence, gradient based optimization algorithms are used to find the model parameters.

Item Type:Papers in Conference Proceedings
Uncontrolled Keywords:implicit; parametric; shape model; disjunctive normal form; Chan-Vese
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
ID Code:28910
Deposited By:Müjdat Çetin
Deposited On:24 Dec 2015 13:28
Last Modified:22 May 2019 13:35

Available Versions of this Item

Repository Staff Only: item control page