Peer-Reviewed Journal Details
Mandatory Fields
Duggan, N,Bae, E,Jones, E,Glavin, M,Vese, L
2014
September
Pattern Recognition Letters
A simple boundary reinforcement technique for segmentation without prior
Published
()
Optional Fields
Image segmentation Convex optimization Variational methods Edge detection Echocardiography images ACTIVE CONTOURS SHAH MODEL ECHOCARDIOGRAPHY DIFFUSION FRAMEWORK MUMFORD
46
27
35
Accurate boundary detection is a critical step of the image segmentation process. While most edge detectors rely on the presence of strong intensity gradients, this criteria can limit robustness in many real world cases. In this work we propose a scheme which makes use of a combination of both global and local segmentation methods to capture the boundary of target objects in low contrast images. This approach has several advantages: the globally convex segmentation scheme is immune from initial conditions and is easily adapted to the data. The addition of a segmentation scheme based on local curve evolution produces a solution which is shown to help preserve topology between the initial and target shape, a property lacking in globally convex segmentation schemes. Experimental results show that the proposed method achieves enhanced performance compared to classical data-driven segmentation schemes proposed in the literature. (C) 2014 Elsevier B. V. All rights reserved.
10.1016/j.patrec.2014.04.014
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