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This paper proposes a novel pose-invariant segmentation approach for left ventricle in 3D CT images. The proposed formulation is modular with respect to the image support (i.e. landmarks, edges and regional statistics). The prior is represented as a third-order Markov Random Field (MRF) where triplets of points result to a low-rank statistical prior while inheriting invariance to global transformations...
Segmentation and tracking of tagged MR images is a critical component of in vivo understanding for the heart dynamics. In this paper, we propose a novel approach which uses multi-dimensional features and casts the left ventricle (LV) extraction problem as a maximum posteriori estimation process in both the feature and the shape spaces. Exact integration of multi-dimensional boundary and regional statistics...
In the paper, we present a novel approach to modeling plants from images by detecting apex features. First, an effective algorithm is proposed to extract apex features in volumetric data recovered from the images. It provides position and pose information for assigning 3D generic leaves. Then, the 3D leaf shapes are determined by an optimization based on the volume. Finally, Branches are modeled by...
We present an approach to decomposing branching volume data into sub-branches. First, a metric is proposed for evaluating local convexities in volumetric data, and it is a criterion for global selection of tip points. Second, a multi-path growing strategy is adopted to segment the volumes based on a DFS transformation starting from the tips. Experiments show that this approach is capable of generating...
We present an algorithm to automatically extract skeletons for branched volumes by shape decomposition. First, a region growing strategy is adopted based on a distance transformation to decompose a volume into several meaningful components with simple topological structures. Then, the skeleton of each component is individually extracted. Finally, the skeletons of all the components are integrated...
The extensive clayization of Dexing copper mine is responsible for water and soil pollutions because of the oxidation of sulfide minerals. During the clayization, harmful elements such as As, S, Sb and Pb could be effectively released into the clay and water. Using the abundant spectral information of short wave infrared (SWIR), combining with the spectral absorbed index, SAM (Spectrum Angle Mapper)...
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