Disjunctive normal shape models

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.

[thumbnail of nRamesh_final.pdf] PDF

Download (421kB)


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
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Electronics
Faculty of Engineering and Natural Sciences
Depositing User: Müjdat Çetin
Date Deposited: 24 Dec 2015 13:28
Last Modified: 26 Apr 2022 09:21
URI: https://research.sabanciuniv.edu/id/eprint/28910

Available Versions of this Item

Actions (login required)

View Item
View Item