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CAIP
2007
Springer

Hierarchical Detection of Multiple Organs Using Boosted Features

9 years 8 months ago
Hierarchical Detection of Multiple Organs Using Boosted Features
Abstract. We propose a framework for fast and automated initialization of segmentation algorithms in Computed Tomography images. Based on the idea that time-consuming voxel classification should be done only on spatially constrained areas, we build classifiers at body and slice levels which quickly define a constrained region of interest. Voxel classification is then performed by a divide-and-conquer strategy using a probabilistic-boosting tree. In addition, this framework can incorporate additional information on the volume, if available, such as the position of another organ to improve its accuracy and robustness. The framework is applied to seed extraction in kidneys and liver.
Samuel Hugueny, Mikaël Rousson
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where CAIP
Authors Samuel Hugueny, Mikaël Rousson
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