title: Self-parameterized active contours based on regional edge structure for medical image segmentation.
abstract: This work introduces a novel framework for unsupervised parameterization of region-based active contour regularization and data fidelity terms, which is applied for medical image segmentation. The work aims to relieve MDs from the laborious, time-consuming task of empirical parameterization and bolster the objectivity of the segmentation results. The proposed framework is inspired by an observed isomorphism between the eigenvalues of structure tensors and active contour parameters. Both may act as descriptors of the orientation coherence in regions containing edges. The experimental results demonstrate that the proposed framework maintains a high segmentation quality without the need of trial-and-error parameter adjustment.
authors.affiliation: Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, 15703 Panepistimiopolis, Athens Greece.
authors.forename: Eleftheria A
authors.initials: EA
authors.lastname: Mylona
authors.affiliation: Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, 15703 Panepistimiopolis, Athens Greece.
authors.forename: Michalis A
authors.initials: MA
authors.lastname: Savelonas
authors.affiliation: Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, 15703 Panepistimiopolis, Athens Greece.
authors.forename: Dimitris
authors.initials: D
authors.lastname: Maroulis
keywords: Active contours; Medical image segmentation; Structure tensors; Unsupervised parameterization