Application of the level-set model with constraints in image segmentation

We propose and analyze a constrained level-set method for semi-automatic image segmentation. Our level-set model with constraints on the level-set function enables us to specify which parts of the image lie inside respectively outside the segmented objects. Such a-priori information can be expressed...

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Bibliographic Details
Published in:arXiv.org 2015-01
Main Authors: Klement, Vladimír, Oberhuber, Tomáš, Ševčovič, Daniel
Format: Article
Language:English
Subjects:
Approximation
Constraint modelling
Image segmentation
Magnetic resonance imaging
Relaxation method (mathematics)
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Summary:We propose and analyze a constrained level-set method for semi-automatic image segmentation. Our level-set model with constraints on the level-set function enables us to specify which parts of the image lie inside respectively outside the segmented objects. Such a-priori information can be expressed in terms of upper and lower constraints prescribed for the level-set function. Constraints have the same conceptual meaning as initial seeds of the popular graph-cuts based methods for image segmentation. A numerical approximation scheme is based on the complementary-finite volumes method combined with the Projected successive over-relaxation method adopted for solving constrained linear complementarity problems. The advantage of the constrained level-set method is demonstrated on several artificial images as well as on cardiac MRI data.
ISSN:2331-8422