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In this paper, we incorporate the concept of Multiple Kernel Learning (MKL) algorithm, which is used in object categorization, into human tracking field. For efficiency, we devise an algorithm called Multiple Kernel Boosting (MKB), instead of directly adopting MKL. MKB aims to find an optimal combination of many single kernel SVMs focus-ing on different(More)
Accurate segmentation of abdominal organs is a key step in developing a computer-aided diagnosis (CAD) system. Probabilistic atlas based on human anatomical structure, used as a priori information in a Bayes framework, has been widely used for organ segmentation. How to register the probabilistic atlas to the patient volume is the main challenge.(More)
BACKGROUND We sought to evaluate a new regional segmentation method for use with three-dimensional (3D) non-contrast abdominal CT images and to report the preliminary results. METHODS The proposed method was evaluated in ten cases. Manually segmented areas were used as the gold standard for evaluation. To compare the standard and the extracted liver(More)
RATIONALE AND OBJECTIVES An atlas-based automated liver segmentation method from three-dimensional computed tomographic (3D CT) images has been developed. The method uses two types of atlases, a probabilistic atlas (PA) and a statistical shape model (SSM). MATERIALS AND METHODS Voxel-based segmentation with a PA is first performed to obtain a liver(More)