Ensemble Learning Based Segmentation of Metastatic Liver Tumours in Contrast-Enhanced Computed Tomography

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Abstract

This paper presents an ensemble learning algorithm for liver tumour segmentation from a CT volume in the form of U-Boostand extends the loss functions to improve performance. Five segmentation algorithms trained by the ensemble learning algorithm with different loss functions are compared in terms of error rate and Jaccard Index between the extracted regions and true ones.

Journal

  • IEICE Transactions on Information and Systems

    IEICE Transactions on Information and Systems 96(4), 864-868, 2013-04-01

    The Institute of Electronics, Information and Communication Engineers

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