Liver tumor detection and segmentation using kernel-based extreme learning machine

@article{Huang2013LiverTD,
  title={Liver tumor detection and segmentation using kernel-based extreme learning machine},
  author={Weimin Huang and Ning Li and Zhiping Lin and Guang-Bin Huang and Weiwei Zong and Jiayin Zhou and Yuping Duan},
  journal={2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
  year={2013},
  pages={3662-3665}
}
This paper presents an approach to detection and segmentation of liver tumors in 3D computed tomography (CT) images. The automatic detection of tumor can be formulized as novelty detection or two-class classification issue. The method can also be used for tumor segmentation, where each voxel is to be assigned with a correct label, either a tumor class or nontumor class. A voxel is represented with a rich feature vector that distinguishes itself from voxels in different classes. A fast learning… CONTINUE READING
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A semi-automated method for liver tumor segmentation based on 2D region growing with knowledge-based constraints

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