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In this paper, a local hybrid level-set method for medical image segmentation is presented. In proposed method, a locally fitted binary energy function is introduced into the hybrid level-set framework proposed by Zhang et al.. Compared with the globally specified threshold, the use of local binary fitting energy in the hybrid level-set method allows one to extract local image information more accurately,...
We present an approach for accurate localization of the neck of intracranial aneurysms and quantification of their geometry that is useful for their treatment through endovascular embolization. In particular, we first obtain a vessel segmentation using a topology-preserving level set method and extract the surface of the segmented vessel. We then separate the aneurysm from the parent vessels and localize...
Segmentation of 3D soft organs from complex volume images is a very important and challenging task. The objects of interest may have inhomogeneous voxel intensities and some object boundaries may be indistinct. Existing algorithms are either sensitive to noise or computationally expensive. This paper presents a novel algorithm that overcomes these shortcomings. The algorithm adopts a novel flipping-free...
This paper studies an new approach to creating a variational level set model for buildings detection by combining LiDAR point clouds and Aerial image data. The level set model introduces an object-based image analysis technique. Firstly, a fundamental object-based level set framework is built by neighbor analysis of remote sensing image. Then, several derived products directly or indirectly from LiDAR...
In this paper we propose a new supervised active contour model evolving with Haralick texture features. This model is divided in two stages. First, we use a supervised step where the user defines an ideal segmentation on a learning image. A linear programming model, modeling the behavior of the active contour, is then used to determine the weights of the Haralick features leading to the optimal segmentation...
This paper presents a level set based segmentation method with shape priors. The shape priors guide the level set deformations so that the contour extraction process is affected not only from the local image properties, but also from the expert knowledge in the form of manual contours. The method does not need an explicit training phase and it does not complicate the level set functional because level...
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