Image segmentation by image foresting transform with geodesic band constraints

Caio de Moraes Braz, P. A. Miranda
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引用次数: 14

Abstract

In this work, we propose a novel boundary constraint, which we denote as the Geodesic Band Constraint (GBC), and we show how it can be efficiently incorporated into a subclass of the Generalized Graph Cut framework (GGC). We include a proof of the optimality of the new algorithm in terms of a global minimum of an energy function subject to the new boundary constraints. The Geodesic Band Constraint helps regularizing the boundary, and consequently, improves the segmentation of objects with more regular shape, while keeping the low computational cost of the Image Foresting Transform (IFT). It can also be combined with the Geodesic Star Convexity prior, and with polarity constraints, at no additional cost. The method is demonstrated in CT thoracic studies of the liver, and MR images of the breast.
基于测地线带约束的图像森林变换图像分割
在这项工作中,我们提出了一种新的边界约束,我们将其称为测地线带约束(GBC),并展示了如何将其有效地合并到广义图割框架(GGC)的子类中。我们包括一个新的边界约束下的能量函数的全局最小的新算法的最优性的证明。测地带约束有助于边界的正则化,从而在保持图像森林变换(IFT)较低的计算成本的同时,改善了形状更规则的目标的分割。它也可以与测地线星凸性相结合,并且具有极性约束,不需要额外的成本。该方法在肝脏的CT胸部研究和乳房的MR图像中得到证实。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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